REAL-TIME BARCODE READER USING PERSONAL DIGITAL
ASSISTANCE (PDA)
OSAMA SALEM ELSHERAIRI
A project report submitted in partial fulfillment
of the requirements for the award of the degree
of Master Engineering
(Electrical-Electronics & Telecommunication)
Faculty of Electrical Engineering
Universiti Teknologi Malaysia
MAY 2007
iii
In the name of Allah, Most Gracious, Most Merciful
All praise and thanks are due to Allah Almighty and peace and
blessings be upon His Messenger
The results of this effort are truly dedicated to my mother and father whose
example as devoted professionals, as well as, parents taught
me to be perseverant, responsible and loyal
to my belief.
To my brothers, and sisters, and my best friend my uncle for all their support,
encouragement, sacrifice, and especially for their love.
Thank you all and this work is for YOU.
iv
ACKNOWLEDGEMENTS
First and foremost, I thank Allah for giving me the strength to complete my
project. I would like to thank especially supervisor ASSOC. PROF. DR. SYED ABD
RAHMAN AL-ATTAS for his constant support and guidance during my graduate
studies at Universiti Teknologi Malaysia. I would also like to convey my deepest
gratitude to Mr. Usman Ullah Sheikh for his guidance to complete this research.
Thanks to all my colleagues and friends with whom I had the opportunity to
learn, and share a good time during my stay here. Finally, special and infinite thanks
goes to the most important people in my life; my parents, for their love, prayers,
sacrifice and support.
v
ABSTRACT
This project concerns the design and implementation of a system for real time
barcode reader using personal digital assistant (PDA) with built-in camera. A system
that reads and decodes (1D) linear barcodes based on images containing barcodes –
independent of the barcodes' orientation or rotation. Problems associated with images
taken by the PDA are limited depth of field, limited resolution, poor lighting
sensitively and camera shake. To accomplish this project with the above constraints
the following stages are undertaken; First the image from the camera is enhanced, the
camera will send continuous frame of images from the environment. These images
are converted to grayscale and some preprocesses are performed, image is filtered
(such as sharpening and noise reduction) and converted to binary. The image is then
scanned horizontally, vertically and diagonally for barcodes, thus enabling it to
detect rotated barcodes to suit the subsequent processing. Then the barcode is located
in the image using a method based on the evaluation of the correlation. To extract
relevant information from the located image the barcode is then isolated from the
image, after that it is used to gain a waveform that represents the information of the
barcode. Finally, the waveform will be wavered into a string of digits representing
the widths of each bars of the barcode. At this stage the processing has completely
decoded the barcode symbology. This project only considers European Article
Number 13, (EAN-13) barcodes. The system has been implemented in Windows
Mobile (windows CE) based software in Embedded Visual Studio 2005 C++ on
PDA, with a graphical user interface. Error correction and predictive decoding is
implemented to improve the capability accuracy and performance of the system.
vi
ABSTRAK
Projek ini berkenaan dengan reka-bentuk dan implementasi sistem kod-bar
maya nyata menggunakan pembantu peribadi digit (PDA) yang dilengkapi dengan
kamera terbina-dalam. Sistem ini mampu membaca dan menyahkod kod-bar satu
dimensi tanpa mengambil kira orientasi dan pusingan kod-bar. Kedalaman medan
yang terbatas, resolusi yang terhad, pencahayaan yang lemah dan goncangan kamera
adalah beberapa masalah yang berkaitan dengan imej-imej yang dihasilkan oleh
kamera PDA. Untuk melaksanakan projek yang mempunyai masalah diatas dengan
jayanya, proses-proses berikut perlu dilakukan. Pertama, kualiti imej ditingkatkan.
Imej-imej ini kemudiannya ditukar kepada imej aras kelabu dan beberapa peringkat
pra-pemprosesan dilakukan seperti penajaman dan pengurangan hingar, dan imej
ditukar ke nombor binary. Untuk mendapatkan kodbar, imej kemudiannya diimbas
secara menegak, melintang, dan pepenjuru untuk menentukan proses yang
selanjutnya. Dengan menggunakan kaedah penilaian korelasi, kodbar diletakkan
didalam imej. Untuk mengekstrak maklumat darapida imej. Kodbar kemudiannya
diasingkan daripada imej, dan digunakan untuk mendapat bentuk gelombang yang
mewakili kodbar. Akhir sekali, bentuk gelombang diliang-liuk menjadi rangkaian
digit yang mewakili lebar setiap buku kodbar. Pada peringkat ini, kodbar telah
dinnyahkod sama-sekali. Projek ini hanya mengambil kira kodbar jenis nombor
artikel Eropah (EAN-13). Sistem ini diatas diimplementasi di dalam persekitaran
Windows Mobile (Windows CE) dengan menggunakan Embedded Visual Studio
2005 C++ untuk PDA dengan antara muka grafik. Pembetulan kesalahan dann
penyahkid penjangkaan dilaksankan untuk meningkatkan ketepatan dan pencapaian
sistem.
vii
LIST OF CONTENTS
CHAPTERS
CHAPTER 1
TITAL
PAGE
DECLARATION
ii
DEDICATION
iii
ACKNOWLEDGEMENTS
iv
ABSTRACT
v
ABSTRAK
vi
TABLE OF CONTENTS
vii
LIST OF TABLES
xi
LIST OF FIGURES
xii
LIST OF ABBREVIATIONS
xv
LIST OF APPENDICES
xvii
INTRODUCTION
1
1.1
Overview
1
1.2
Personal Digital Assistant (PDA)
2
1.2.1 Pocket PC
3
1.3
Plam
4
1.4
Smartphones
4
1.5
Camera used with PDA
5
1.6
Windows Mobile
5
1.7
PDA using a camera
6
1.8
Limitation of conventional barcode readers
7
viii
CHAPTER 2
1.9
Objective of Project
8
1.10
Scope of Project
8
1.11
Project outline
8
LITERATURE REVIEW
10
2.1
Introduction
10
2.2
A bit of history
11
2.3
Types of Barcodes
11
2.3.1
One Dimensional barcodes
12
2.3.2
Two - Dimensional barcodes
13
2.4
2.5
2.6
CHAPTER 3
The Physical Reader
13
2.4.1
Input Device
14
2.4.2
Decoder
18
2.4.3
Barcode Reading
19
The Barcode Recognition System
21
2.5.1
EAN-13 Barcode Image Recognition
21
2.5.2
Barcode symbologies
21
2.5.3 Barcode Size and Color
22
Encoding Rule of Structure of an EAN barcode
23
2.6.1
The X-dimension
24
2.6.2
Quiet zone
24
2.6.3
Guard bars
25
2.6.4
Right & left hand side digits
26
2.6.5 How to calculate the checksum
27
2.6.6
Encoding
28
2.6.7
Decoding
31
METHODOLOGY
32
3.1
Introduction
32
3.2
Barcode Image Devices
33
ix
3.3
Image Capturing
33
3.4
Barcode processing in PDA
34
3.4.1
35
Searching for barcode image
automatically
3.4.2
Identification of the Bars and Spaces
36
3.4.3
Estimating How Correctly the Elements
36
Have Been Identified
3.4.4
3.5
Decoding the Barcode
37
Pre-Processing
38
3.5.1
39
The RGB color model
3.5.2 Gray scaling
40
3.5.3
41
Image Enhancement
3.6
Scanning Direction
42
3.7
Barcode Identification & Extraction
44
3.8
Program Architecture
45
3.8.1
45
Overview of Programming Languages
Used For PDA
3.8.2
3.9
CHAPTER 4
Program Build on PDA
46
Program screenshot
46
3.9.1
Program interface
47
3.9.2
Using the HP Photosmart Mobile Camera
48
RESULT
50
4.1
Introduction
50
4.2
Uneven Resolution, Shadow, Shake and
50
Illumination
4.3
Tests of Barcode Orientation
51
4.3.1
52
Computing the orientation of the barcode
4.4
Show scan diagonal read rotated barcode (offline)
53
4.5
Show scan horizontal read rotated (offline)
54
4.6
Show scan vertical read rotated barcode (offline)
54
x
4.7
Show scan horizontal read rotated barcode
55
(online)
4.8
Time Consumption
56
4.9
Performance Comparison
56
CHAPTER 5 CONCLUSION
58
5.1
Conclusion
58
5.2
Recommendations for Future Work
58
REFERENCE
59
APPENDIX
63
xi
LIST OF TABLES
TABLE
TITAL
PAGE
2.1
Specification for EAN-13 barcode
22
2.2
Total number of bars and modules for EAN-13 barcode
28
2.3
The list of oriented-modules on logic of 0-9 for A, B, C,
29
types
2.4
Result for example
30
3.1
Normal barcode (left to right)
37
3.2
Flipped or mirrored barcode
38
3.3
These are classes used in program
46
xii
LIST OF FIGURES
Figure
TITAL
PAGE
1.1
Symbol barcode
2
1.2
HP iPAQ hx4700 Pocket PC
3
1.3
Palm
4
1.4
Smartphone
4
1.5
Digital camera card (HP Photosmart mobile camera)
5
1.6
Different devices used windows CE
6
1.7
Interfaces for windows CE
6
1.8
PDA build-in camera
7
2.1
A scheme of a bar code reading system
10
2.2
Numeric barcode, 1D
12
2.3
Alphanumeric barcode, 1D
13
2.4
Some types of barcode, 2D
13
2.5
Reader (a), Laser scanner, (b) CCD scanner, (c) CCD
15
sensor by a lens.
2.6
Pen-Type readers
15
2.7
Some cameras can used to read barcode
16
2.8
These are some digital camera card (Photosmart mobile
16
camera)
2.9
The barcode reader with PDA in the shopping
17
2.10
Barcode EAN-13
21
2.11
(a) equivalent EAN-13 barcode, with the first character
22
set to zero, and (b) an EAN-13 with an additional digit
used, with the first character set to not zero
xiii
2.12
X-dimension barcode
23
2.13
Barcode Structure
24
2.14
Actual size of EAN-13
25
2.15
EAN-13, left and right hand
29
2.16
Barcode EAN-13 Parity Encoding
30
3.1
Architectural Overview: Our EAN-13 barcode and
33
resolution system consists of a PDA using camera and
load from file application for decodes barcode
3.2
There are some progress used to read barcode
33
3.3
Image processing in PDA
34
3.4
Some symbols barcode image
35
3.5
Schematic of the RGB color cube
39
3.6
Illustrating difference between a general RGB color
40
image and a general gray scale image.
3.7
Original gray-scale image
40
3.8
A 3x3 window, for use in a windowing function, where
42
the z-values corresponds to the gray-scale values of the
original image
3.9
Spatial filters (a) Gaussian Blur, (b) Laplacian (c)
42
Sharpen
(d) Unsharpen Mask
3.10
Scan 4 directions implemented
43
3.11
These are some direction of a barcode at different angles,
43
(a) Horizontal (b). Vertical (c) Diagonal (d) invest
horizontal
3.12
Illustrating how the barcode's angle µ is derived using the
44
vector displacement, k, the distance d between two
vectors, and basic trigonometry.
3.13
Steps to identify and extract the EAN-13 barcodes
44
3.14
program interface
47
3.15
Getting Acquainted
48
xiv
4.1
These are some samples for barcodes image are not clear,
51
all of them (uneven resolution and shake)
4.2
Some types of barcode all of them very clear
51
4.3
Some types of barcode all of them not clear
51
4.4
Shows the output from the localization algorithm. Angle
52
α is the angle of the bar code. The angle is also given by
90 - β
4.5
Rotation
53
4.6
Diagonal (+45, - 45), (a) scan consume operation
53
93ms,(b) scan consume 1482ms, (c) scan consume
operation 617ms
4.7
Horizontal, (a) scan consume operation 531ms,(b) scan
54
consume 492ms, (c) scan consume operation 462ms
4.8
Vertical, (a) scan consume operation 435ms,(b) scan
55
consume 336ms, (c) scan consume operation 515ms
4.9
some tests from camera (online), (a) scan consume
55
operation 203ms,(b) scan consume 270ms, (c) scan
consume operation 272ms
4.10
compare consume operation
57
xv
LIST OF ABREVIATIONS
PDA
-
Personal Digital Assistants
GPS
-
Global Positioning System
PC
-
Personal computer
MS
-
Microsoft
RAM
-
Random access memory
CPU
-
Central processing unit
GSM
-
Gold Standard Multimedia
GPRS
-
General Packet Radio Service
CDMA
-
Code division multiple access
WCDMA
-
Wideband Code Division Multiple Access
3G
-
3-Generation
SD
-
Secure Digital
MP
-
Micro Pixel
D
-
One- or Two- Dimensional
BMP
-
Windows Bitmap
EAN
-
European Article Number
UPC
-
Universal Product Code
CCD
-
Charge-Coupled Devices
PSA
-
Personal Shopping Assistant
PIM
-
personal information manager
JPEG
-
Joint Photographic Experts Group
RGB
-
Red, Green and Blue
SD
-
Secure Digital
SDIO
-
Secure Digital Input/Output
SDK
-
Software Development Kit
xvi
PCB
-
Printed Circuit Boards
CD
-
Compact Disc; conjugate directions
GSM
-
Groups :Special Mobile or Global System for Mobile
SMS
-
Simplex Minimization Search
xvii
LIST OF APPENDICES
APPENDIX
TITAL
PAGE
A
Camera SDIO SDK Specification
63
B
Visual Studio 2005 C++ CLASS DECLARATION
70
C
Some Types of digital camera card
75
D
SOME BARCODE IMAGE ARE VERY CLEAR
79
E
SCREENSHOTS OF COMMERCIAL TEST
80
PROGRAMS
F
Number System (number of countries)
82
CHAPTER 1
INTRODUCTION
1.1 Overview
Today barcodes are present all around us not only for use on groceries in the
super-market, but also in industries for example in a car assembly plant most the car
parts are marked with barcodes for identification purposes. Similarly, and for the
same reasons, most electronic circuits and microchips have barcodes on them.
Why is that? Why are barcodes used?
The main reason is the convenience and effectiveness barcodes provide since
they are designed for automated reading and interpretation. Leading to a
rationalization when a machine does the job instead of a human operator. Further, a
product can be given a fix barcode, only linking the barcode’s number to a database
containing attributes such as price, manufacturing date, adjacent bars and spaces
etcetera. Hence, attributes can easily be changed in the database, without actually relabeling the product.
Barcodes are standardized, as shown in figure 1.1, which leads to that they
are consistently shaped and used, and that they have a well defined structure
wherever they are found.
They provide unambiguous, and secure, identification. Some barcode
symbologies also offer a feature for tracing for example the origin of a product. As
2
barcodes are wide-spread over the world there has naturally evolved many different
ways to read them – using for example laser scanners, so called wands, CCDscanners, or digital cameras. If it could be possible to use personal digital assistant
(PDA) build in camera to read barcodes image much could be gained. Naturally, the
first advantage compared to, for example, a laser scanner is that the object with the
barcode is visible in the image, and thus that the operator can see whether the object
is for example intact or damaged, which means that the system easily could be
expanded with additional cameras. This is due to the fact that the PDA using a
camera downloads the images with ease could be connected to the network via the
internet such as the World Wide Web.
Figure 1.1: symbol barcode
1.2 Personal Digital Assistants (PDA)
A personal digital assistant (PDA) is a handheld device technology that can
implements various new kinds of applications such as telephone/fax, internet, GPS,
movie and network features. A typical PDA can function as a cellular phone, fax
sender, Web browser and personal organizer. Unlike portable computers, most
PDA’s began as pen-based, using a stylus rather than a keyboard for input. This
means that they are also integrated with handwriting recognition features. Some
PDA’s can also react to voice input by using voice recognition technologies. PDA’s
of today are available in either a stylus or keyboard version.
3
1.2.1 Pocket PC
This project will use Pocket PC (HP iPAQ hx4700 series as shown in Figure
1.3). The main reason for choosing Pocket PC rather than Palm is that Pocket PC is a
handheld computer with a subset of the capabilities of a PC and provides the basic
functionality those users need when they are traveling. Pocket PC also has a longer
battery life than a notebook PC, therefore, offers 320 x 240 color display or more,
moreover it can use touch screen for data entry. The pocket PC uses a cable serial &
USB sync port to connect with PC or other devices. It is an available compact flash
and/or Secure Digital (SD) Card for secondary storage. The pocket PC is better than
palm because the palm is just an organizer but the Pocket PC is a small computer that
uses a windows interface which is already user-friendly. The Pocket PCs are more
popular and used by many people because it can use Microsoft Word, Excel, and
Outlook. The Pocket PC uses high resolution color screens.
Pocket PCs come with mobile versions of office applications in addition to
Microsoft Outlook Mobile. Though there are different Pocket PCs, all of them can
compose e-mail messages and send them by synchronizing with desktop computer or
wirelessly.
Figure 1.2: HP iPAQ hx4700 Pocket PC
4
1.3 Palm
The palm has some applications with an easy to use interface, as shown in
figure 1.3
Figure 1.3: Palm
1.4 Smartphones
Mobile phones use Windows Mobile or Symbian as operating system
developed by the Palm Company. The smartphone is different with PDA’s, as shown
in figure 1.4.
Figure 1.4: Smartphone
5
Therefore, the smartphone has something like a PDA (storage on flash,
multimedia features, pocket outlook, pocket internet explorer, GSM/GPRS,
CDMA, WCDMA, 3G Radio, SD Card.
1.5 Camera used with PDA
There are many kinds of camera for PDA. They include; built–in camera,
wireless camera and digital card camera. The recent models of smartphone’s and
PDA’s have built-in camera, as shown in figure 1.5, which is digital camera card that
can be used in a PDA’s and other dives.
Figure 1.5: Digital camera card (HP Photosmart mobile camera)
1.6 Windows Mobile
Microsoft recently announced Windows Mobile operating system, which is a
handheld device powered by the Windows Mobile platform. It allows the user to
make phone calls, retrieve e-mails, browse the Internet, send and receive text
messages, read and compose Microsoft Word Mobile files, make Microsoft Excel
Mobile charts, and view Microsoft PowerPoint presentations. Windows Mobile
powered devices come in three types and includes: Pocket PC, Pocket PC Phone
Edition, and Smartphone, as Shown Figure 1.6
6
Figure 1.6: Different devices that use windows CE
Windows CE (WCE) is a Windows like operating system for various
handheld devices, including Personal Digital Assistants (PDA’s) and Mobile Phones.
While at the API level, many of the function calls and interfaces are the same as the
standard version of Windows as shown in figure 1.7, much of the internals have been
altered to accommodate many different types of CPUs and architectures.
Figure 1.7: Interfaces for windows CE
1.7 PDA using a camera
The system architecture of PDA using a camera is a recent generation of PDA
devices, as shown in figure 1.8
7
Figure 1.8: PDA build-in camera
This project can perform either in real-time (online) or load from a file
(offline). The application revolution has been made possible by the added extra
processor called an application processor into the newer PDA's. The software used is
Embedded Visual Studio 2005 C++ and the hardware system processing will be done
in real-time by PDA using camera. See figure 1.8, PDA with camera.
1.8 Limitations of Conventional Barcode Readers
In real time (online) phase, the capturing of barcodes image depends on the
following:
a) Resolution of the camera, for build-in camera in real time, the resolution
of the camera must be more than 3.0 MP.
b) Light intensity is very important to camera.
c) Camera stationary using a camera that is shaking will could the barcode
image to be blurred (that mean the bars are not clear.).
8
1.9 Objective of Project
The main objective of this project is to develop a system comprising of a
PDA using camera and software for the purpose of capturing 1-D barcodes and
decoding them in real-time (online) as well as offline (reading from a file). Suitable
image processing techniques must be implemented in the software to accommodate
inaccuracies or environmental changes during the acquiring process.
1.10 Scope of Project
The project is mainly to develop a Windows Mobile (windows CE) based
software in Embedded Visual Studio 2005 C++, which is to be run on HP Ipaq hx
4700 series PDA.
a. The program obtains images barcode from offline windows bitmap (BMP)
files or in real-time from a camera that is either attached or built in the PDA.
b. The image barcode is obtained from a camera that is either attached or built
in the PDA.
c. Barcode symbologies that will be considered in the project will be mainly the
EAN -13 (Very common in consumer products).
1.11 Project Outline
This project is organized into five chapters. The outline is as follows;
Chapter 1-Introduction
This chapter discusses the objectives and scope of the project and gives a
general introduction to barcode technology.
9
Chapter 2-Review of Literature Studies
This chapter reviews the relevant literature and previous work regarding PDA
using camera barcode readers. In addition to that, explain of EAN-13
symbologies are given.
Chapter 3- Methodology
This chapter elaborates on the principles behind good quality image
acquisition and the factors that must be taken into consideration to obtain
readable barcodes. This includes camera selection, determination of field of
view, resolution, light intensity and shake. The algorithms to initiate barcode
detection and decoding are also described and justified in this chapter.
Chapter 4-Result
The final results of this project are shown in this chapter.
Chapter 5-Conclusion
This chapter consists of the conclusion and future improvement.
CHAPTER 2
LITRATURE REVIEW
2.1 Introduction
There is quite a number of research works carried out on barcode reading and
localization using camera. Findings of these works are described in this chapter. This
chapter will also present an explanation of the barcode EAN-13 symbologies.
Barcodes are information carrying graphical patterns designed for easy and
reliable automatic retrieval. The most common barcodes are known as onedimensional barcodes. These graphical patterns in a single dimension (e.g.
horizontal), and are constant in the other (vertical) dimension and diagonal
dimension. In order to convey more information on the same surface area, the
constancy in the vertical dimension has to be abandoned for more intricate patterns,
known as two-dimensional barcodes.
Barcode reader is to extract the optical information in a symbol from bars and
spaces into computer-compatible data. The data can either be transmitted directly. A
general scheme for a bar code reading system is shown in figure 2.1.
Online or
Offline
Processor
Decoder
Figure 2.1: A scheme of a barcode reading system
Code
Barcode
11
2.2 A bit of history for Barcode
Beginning with 1932, when an ambitious project was conducted by a small
group of students headed by Wallace Flint at the Harvard University Graduate
School of Business Administration. The project proposed that customers select
desired merchandise from a catalog by removing corresponding punched cards from
the catalog.
Barcode was first used commercially in 1966, however, it was soon realized
that there would have to be some sort of industry standard set. [3] By 1970, the
Universal Grocery Products Identification Code or UGPIC was written by a company
called Logion Inc. The first company to produce barcode equipment for retail trade
use (using UGPIC) was the American company Monarch Marking in 1970, and for
industrial use, the British company Plessey Telecommunications was also first in
1970. UGPIC evolved into the U.P.C. symbol set or Universal Product Code, which
is still used in the United States. George J. Laurer is considered the inventor of
U.P.C. or Uniform Product Code, which was invented in 1973. In June of 1974, the
first U.P.C. scanner was installed at a Marsh's supermarket in Troy, Ohio. The first
product to have a barcode included was a packet of Wrigley's.
2.3 Types of Barcodes
To understand the contents of barcodes or be able to produce own barcodes
one has to understand the barcode symbology. The symbology is very much a like a
language defining how different combinations of various wide bars and spaces shall
be interpreted. There are many different barcode symbologies, one- dimensional or
two-dimensional, fixed-width or multi-width, each with various properties such as
data density or type of data stored, all designed to fulfill a specific purpose [1, 2].
The symbology also defines properties such as:
•
Quiet Zone, a quiet area around the barcode to avoid interference with
surrounding textures.
12
•
Start and Stop Patterns, speeds up the localization of the barcode.
•
Aspect Ratio, defines the relations between width and height of the whole
symbol and the different widths of bars and spaces.
•
Parity and Redundancy, ensures a low error rate and enables damaged
barcodes to be read.
Bar code systems can use several symbologies. A symbology is equivalent
to a language. Each symbology has strengths and weaknesses. Many symbologies are
around for historical or political reasons, while others have definite technical
advantages.
2.3.1
One Dimensional barcodes
It is employed in low information content applications like product index
registry (e.g. automatic price tagging and inventory management), or serial number
registry (e.g. test-tube tagging in automated medical tests). Two-dimensional
barcodes are used in applications that require more information contents like mail
addresses (for automated mail reading and distribution systems), or compressed
content of a printed page (to avoid the need for optical character recognition), as
shown in figure 2.2 and figure 2.3.
a. Numeric-only barcodes
EAN-13
EAN-8
UPC-A
Figure 2.2: Numeric barcode
UPC-E
13
b. Alphanumeric barcodes
Code-39
code-93
code-128
Figure 2.3: Alphanumeric barcode
2.3.2 Two - Dimensional barcodes
It is graphical patterns composed usually of dots. They are rendered using
two-toned dots (e.g. black dots on a white background), and occupy, usually a
rectangular area. Two-dimensional barcodes incorporate various registration and
fiducially marks, enabling automated identification, and accurate registration of the
barcode, which might be read-in in arbitrary orientations. In addition, two
dimensional barcode systems employ various error correcting codes for reliable
automated retrieval, as shown in figure 2.4.
PDF 417
DataMatrix
Maxicode
QR code
Figure 2.4: Some types of barcode, 2D
2.4 The Physical Reader
A physical barcode reader is considered to contain two separate elements: the
input device and the decoder [3]. These two elements can either be separated into
two different physical units or they can both be in one single unit. The input device
14
includes the electro-optical system and the camera system, while the decoder equals
the processor.
2.4.1 Input Device
There are different ways to read a barcode: by a scanner, using a wand or a
vision-based `device [2]. All these devices share a common structure in how the
reading process is performed. The user either holds the reader over the barcode or
holds the barcode image in front of the reader. All approaches scan a line across the
barcode and measure the intensity along the scan line. High intensity corresponds to
a bar and low intensity corresponds to a space. If the scan line does not cross the
entire bar code, the code will not be read. Then, another line must be scanned such
that the barcode is converted. The user has to ensure that the scan line is in the right
direction and that it covers the entire bar code [1].
a. Scanner
A scanner is usually a handheld device and is often used in the retail industry. In
some cases, the scanner is stationary and the user places the barcode in front of
the beam, like in the supermarket [1, 2], as shown in figure 2.5.
The scanner either moves the beam over the code by itself or the user has to
move the beam over the barcode. In the second case, the user has to be able to move
his hand with some skill.
The handheld device must stay at the same distance from the barcode while
the beam is moved over the code. A scanner does not have contact with the barcode.
A handheld, moving beam scanner has a large advantage over a fixed beam scanner.
It can scan with a much higher frequency, up to 40 scans per second, and almost no
operator skill is required. There is another type of handheld scanner that uses a raster
laser scan pattern to read 2D symbols.
15
(a)
(b)
(c)
Figure 2.5: Reader (a). Laser scanner, (b) CCD scanner, (c) CCD sensor by a lens.
b. Wand
A wand is a handheld device with a fixed beam that physically touches the
barcode is shown figure 2.6. The reading device of the wand is in the tip and the
wand looks like a pen that is moved over the barcode. The user has to provide the
moving motion of the beam, and therefore, some operator skill is required to use
a wand. The hardest thing is to move the wand at the right speed and to not make
too high accelerations [1, 3].
Figure 2.6: Pen-Type readers,
c. Vision-Based Scanning
Vision-based scanners use a camera to read the barcode, as shown figure 2.7. An
image is taken over the barcode area and is then analyzed so that the code can be
decoded. This technique has an advantage over the others when reading 2Dsymbols. It is not as fast but more accurate and thus better to use in some
applications, than the other two techniques. The performance and symbols
available for decoding have been evaluated [3].
16
Figure 2.7: Some cameras can used to read barcode
However, there are many kinds of a camera using with other devices. There
are built–in cameras, wireless camera and digital card camera, as shown Figure 2.8
The most of modern smartphone’s and PDA’s have built-in camera. This the camera
usually used with PDA to take a picture, video, etc.
Figure 2.8: These are some digital camera card (Photosmart mobile camera)
Wesley Chan [9], Project Voyager builds applications that link virtual
services to people, places, and things see figure 2.9. This is describes the design and
implementation of two such systems. The MIT Campus Guide application provides
services for specific points of interests. Campus visitors used the system to interact
with different sites, for example, a restaurant, a lecture hall, or a sculpture. The
Voyager Personal Shopping Assistant (PSA) connects shoppers in a supermarket to
17
virtual services, linked to specific products. Customers used handheld computers to
scan products. The system retrieved relevant information from the Internet about
each item, including recipes, nutritional information, and related product
recommendations. Project Voyager successfully deployed both systems and
conducted informal user trials.
Figure 2.9: The barcode reader with PDA in the shopping
Peter Sundström [3]. Barcode Reader for Surface Mounting Systems This is
describes a method for reading barcodes with a camera that has a field of view that is
smaller than the size of the barcode. The method analyzes partial barcode images.
From these images the barcode area is located and decoded. Using partial images
when reading barcodes is quite unique. The method reads the barcode EAN13 in two
steps. In the first step the partial barcode images are analyzed and a region of interest
is detected. The partial barcode images are then merged to one large image with one
region of interest. The barcode area is located by finding regions that have a high
concentration of mono-oriented gradients. In the second step, an average of lines is
scanned across the region of interest of the bar code. A waveform is produced that
has ridges and valleys. Ridges correspond to bars and valleys correspond to spaces in
the barcode. The width of the bars and spaces are classified and decoded so that the
bar code data can be extracted. Both code 128 and code 39 can be decoded. The
developed method has been tested on a set of bar code images. From a test set of 13
undamaged bar codes all were decoded correctly but from a test set of 11 damaged
18
bar codes 50 % were decoded correctly. The bar code area is correctly located in 90
% of all the partial bar code images.
2.4.2 Decoder
As mentioned before, the decoder analyzes the signal from the input device
and deciphers the information encoded in the barcode. The data is either transmitted
to an attached PDA, stored locally for later transfer, or forwarded to an application
program in the decoder itself. All decoders have a system that decodes the encoded
symbols information to understandable data. This system is usually implemented in
software on a microprocessor, but it might also be implemented in hardware. There
are some basic steps included in all decoders [2]:
1. Measure the width of each element or the edge-to-similar-edge distance,
depending on the symbol. Only for CCD input devices the actual distance is
measured. Instead, the decoder measures the time the signal spends in an
element.
2. Quantize the element widths to fit the symbol description. This is hard if the
input device does not have a moving beam.
3. Decode the quantized element characters to readable data. This is done via a
look-up table.
4. If necessary, reverse the order of the decoded data characters to accommodate
symbols that have been scanned in the wrong direction.
5. Perform additional checks to confirm the validity of the scan. Such as: quiet
zone size,check character...
6. Transmit the decoded data.
19
2.4.3 Barcode Reading
Usman Ullah Sheikh [1], real-time barcode reader using Active vision. This is
to decode the UPC-A and EAN-13 barcodes using an active vision system, consisting
of a camera and user-written software. The camera will feed the software with
continuous frames of images from the environment. These images are converted to
grayscale and some preprocessing is performed. Image is filtered (such as sharpening
and noise reduction) and converted to binary. An adaptive thresholding algorithm is
used to reduce the effects of uneven illumination. Image is then scanned horizontally,
vertically and diagonally for barcodes, thus enabling it to decode rotated
barcodes.Error correction and predictive decoding is implemented to improve the
speed and accuracy of the system. Overall system performance is benchmarked with
existing commercially available software.
Johan Bylund, Fredrik Jirhede [2],Visual Barcode Reading, the design and
implementation of a system for visual barcode reading, using a network camera A
system that reads and decodes linear barcodes based on images containing barcodes
– independently of the barcodes' orientation or rotation. To accomplish this method
based on various image and signal processing was developed, consisting of the
following main stages. First the image from the camera was enhanced, using Sobel
filters, to suit the succeeding processing. Then the barcode was located in the image
using a method based on the evaluation of the correlation between small parts of the
image. To extract relevant information from the located image the barcode was then
isolated in the image. After that the Hough transform was used to gain a waveform
representing the information of the barcode. The waveform was then subjected to
various processing resulting in a string of digits representing the width's of the
elements of the barcode. To this stage the processing has been completely barcode
symbology independent, which implicates that many symbologies could be included
parallelly in the succeeding stage. However, of practical reasons only EAN-13
barcodes were considered in the final decoding stage; where symbology specific
information was used to normalize the informa- tion, decode the information, and
validate the result using a checksum. The system was implemented in C on a PC
running Linux, with a graphical user interface written C++. The all over performance
was good, and all predefined objectives were met to full satisfaction. Key-words:
20
Barcode decoding, barcode symbologies, network camera, image processing, image
enhancement, Sobel operator, barcode localization, pattern recognition, feature
extraction, Hough transform.
Douglas Chai and Florian Hock [13], Locating and Decoding EAN-13
Barcodes from Images Captured. Digital Cameras by a vision-based technique to
locate and decode EAN-13 barcodes from images captured by digital cameras. The
ultimate aim of our approach is to enable electronic devices with cameras such as
mobile phones and Personal Digital Assistants (PDAs) to act as a barcode reader.
Yasser Ebrahim, Wegdan Abdelsalam, Maher Ahmed, Siu-Cheung Chau,
Proposed a Hybrid Tag-Camera-Based Identification and Navigation Aid for the
Visually Impaired, a barcode-based system to help the visually impaired to identify
objects in the environment and navigate through unknown territories is introduced.
The system is based on the idea of tagging the different objects with 2D barcodes,
with the aid of a portable camera and a computing device. The system can recognize
and relay the barcode content to the user. The advantages of the proposed system
compared to those of existing technologies. This paper addresses the self-localization
problem from a pragmatically point of view since it argues for using passive artificial
landmarks in order to support mobile robot localization in indoor environments. The
idea is to further improve already existing localization capabilities by providing
relevant environmental spots with semantic information. In order to facilitate the
detection of these landmarks the employment of bar codes is proposed. Experimental
results concerning the detection and identification of barcode labels by means of
vision have been presented [24]. The BCReader is a new product for smartphones
that gives possibility to decode barcodes from snapshots made by onboard camera.
Simply make photo of barcode on selected thing and save received data in phone’s
database for further processing. For each barcode BCReader can save title name,
price and description. The BCReader allows searching necessary goods and
comparing their prices in different stores to make best choice [27].
21
2.5 THE BARCODE RECOGNITION SYSTEM
2.5.1 EAN-13 Barcode Image Recognition
The European Article Numbering system (EAN) is by far the most popular
barcode used in the retail industry. It’s available on almost all consumer products.
While the EAN code format was adopted 3 years later. There are several versions
EAN-13 barcodes, such as EAN-13 (13 digits).While EAN-13 is the equivalent for
the European market. Thus, the structure and size are the same. The EAN-13 encodes
12 digits of numeric message and one check digit to form a 13 digit barcode. The
check digit is not a part of the data, but merely for error checking [3].
Figure 2.10: Barcode EAN-13
2.5.2 Barcode symbologies
Barcodes are like a printed version of the most code. Different bar and space
patterns are used to represent different characters. Sets of these patterns are grouped
together to form a "symbology". There are many types of barcode symbologies each
having their own special characteristics and features. Most symbologies were
designed to meet the needs of a specific application or industry. However, for the
EAN-13 symbology, the data is encoded differently, where the first two digits
represents the country of origin. The last digit is still the check digit, while the
remaining digits are composed of manufacturer’s number and product’s number.
There are differences between these two symbologies. The EAN-13 barcode
when the first character is set to 0. Visually looking at the bars of Figure 2.11.a and
Figure 2.11 b, both barcodes are identical. In other words, a digit EAN-13, if the first
22
digit is set to 0. EAN-13 “0-XXXXXX-XXXXXX”. Both barcodes are made of left
and right-hand character sets. The EAN-13 encodes a 13th digit into the parity pattern
of the left six digits symbol (EAN-13 = Data Structure + Symbology) [1].
(‘0’+11+1 Characters)
(12+1 Characters)
Symbology
L
R
L
R
Data Structure
(a)
(b)
Figure 2.11: (a) equivalent EAN-13 barcode, with the first character set to zero, and
(b) an EAN-13 with an additional digit used, with the first character set to not zero
2.5.3 Barcode Size and Color
The size in an EAN-13 barcode is at three different magnifications. Barcodes
can be a scaled to a minimum of 80% of the standard dimension, and up to 200% [1].
The complete specification is given in table 2.1.
Table 2.1: Specification for EAN-13 barcode
29.83 mm x 20.73 mm
Minimum size
74.58 mm x 51.82 mm
Maximum size
37.29 mm x 25.91 mm
Nominal dimensions
0.330 mm
X-dimension at normal size
80% to 200% from normal dimension
Magnification factor
Left 3.63 mm (11x), Right 2.31 mm
Quiet Zone
(7x) Top &Bottom 0.33 (1x)
22.85 mm at nominal size
Bar height
Rear lower right quadrant
Target location
23
2.6 Encoding Rule of Structure of an EAN barcode
The EAN-13 standard, consist of a number of printed bars with intervening
spaces. The characters within the symbology are encoded in a pattern with various
sizes of narrow and wide, bars and spaces. There are two different types of a barcode
depending on where it is marked. The first type is recognized as "source marking".
The barcode of this type is marked on the product during manufacturing process. The
second type is a recognized as "in-store marking". Products of this kind are only sold
in some particular stores. It is extensively used by most of the commercial products.
There are total of 13 digits in an EAN-13 code. The center pattern and the guard
pattern consist of auxiliary characters, see figure below.
Figure 2.12: Barcode Structure
In this standard, each digit is composed of 7 modules. The center pattern and
the guard pattern contain 5 modules and 3 modules, respectively. The first three
digits of an EAN-13 code are country prefix, see figure 2.12. They are used to
identify the nationality of the organization issuing the barcodes. Their four
successive digits represent the manufacturer number. Then, the five successive digits
represent the specific product item number. The last digit of an EAN-13 code is a
check digit. In this standard, a code consists of 7 modules. Different combinations of
011 will represent different numbers under this format. There are total of three
24
encoding rules for the so-called A, B, C types. Based on these encoding rules, we can
decode a bar code into its corresponding digits easily. In the EAN-13 standard, the
selection of encoding rule totally depends on the first digit of the country prefix. The
whole barcode is made of predefined standard elements [3].
2.6.1 The X-dimension
The X-dimension or module is the width of the narrowest bars or spaces in
the barcode [27-28]. The width of the other bars or spaces is two, three or four times
the size of X-dimension, see figure below. The X-dimension is 264μm, 330μm and
660μm for a barcode scaled at 80%, 100% and 200% respectively. The X-dimension
and the width of the thickest bar cannot be more than four times the width of Xdimension. Any barcode will be divided to a spatial, then, each spatial has two bars
(black is present (zero)) and two spaces (white is present (one)), after that, it will be
divided to 7-dimension, then, it will get a digital numbers from it [1].
Figure2.13 : X-dimension barcode
2.6.2 Quiet zone
Quiet zones are the areas to each side of the code that must be kept clear. The
blank areas are before/after the barcode [1, 3, 28]. It is measured in terms of “n”
times the narrowest bar size (X-dimension). The quiet zones for an EAN-13 barcode
25
are 11 modules on the left hand side (Figure 2.14(1)), 7 modules on the right hand
side (Figure 2.14(2)), and 1 module thickness each at the top and bottom of the
barcode (Figure 2.14(3), Figure 2.14(4)). The end of the barcode on the right hand
side is usually marked with an indicator ‘>’, indicating the end of quiet zone (Figure
2.14(11)).
2.6.3 Guard bars
A guard pattern is placed on the right, at the center and on the left of the
barcode. This pattern is required so that the reader can identify the starting point of a
particular barcode (Figure 2.14(5), Figure 2.14(7), Figure 2.14 shows) the starting
and ending guard bars in the order of Black-White-Black (3 bars, each 1 module
thick). A centre guard is placed in the middle of the barcode. The centre guard has
the same convention as the side guards. Figure 2.14(7), the center guard bars in the
order of White-Black- White-Black-White (5 bars, each 1 module thick).
Figure 2.14: Actual size of EAN-13
26
2.6.4 Right & left hand side digits
It consists of four areas; normally the number system digit is printed to the
left of the barcode, and the check digit to the right. The manufacturer and product
codes are printed just below the barcode, separated by the guard bar.
a. Number System
The number system consists of two digits (sometimes three digits) which identify
the country/region numbering authority which assigned the manufacturer code.
Any number system which starts with the digit 0 is a UPC-A barcode. The
number system list is maintained by EAN organization. Also, the number
systems for every country/region are listed (in last chapters).
b. The Manufacturer Code
The manufacturer code is a unique code assigned to each manufacturer by the
numbering authority indicated by the number system code. All products produced
by a given company will use the same manufacturer code. EAN uses what is
called "variable-length manufacturer codes." Assigning fixed-length 5-digit
manufacturer codes, means that each manufacturer can have up to 99,999 product
codes--and many manufacturers don't have that many products, which means
hundreds or even thousands of potential product codes are being wasted on
manufacturers that only have a few products. Thus if a potential manufacturer
knows that it is only going to produce a few products, EAN may issue it a longer
manufacturer code, leaving less - space for the product code.
This results in more efficient use of the available manufacturer and product
codes.
c. The Product Code
The product code is assigned by the manufacturer. The product code immediately
follows manufacturer code. The total length of manufacturer code plus product
code must be exact 10 digits.
27
d. The Check Digit
The check digit is used to verify that the barcode is generated or scanned
correctly. The check digit is calculated based on the rest of the barcode digits.
Since a scan can produce incorrect data due to inconsistent scanning speed, print
imperfections, or a host of other problems, it is useful to verify that the rest of the
data in the barcode has been correctly interpreted.
2.6.5 How to calculate the checksum
The check digit is a character included with the symbol to check on the validity
of a barcode’s data when decoding. In the previous section, the check digit was
assumed available. However, in the actual encoding process, the check digit is
calculated based on the data to be encoded. The process of calculating the check digit
is given below:
1. Multiply all odd digits with 3 (the first digit is even).
2. Add all the even digits with the multiplied odd digits.
3. Add a number X to the sum, so that it is evenly divisible by 10.
4. The number X is the check digit.
Example: Assume the data to be encoded is; data = 7-501031-31130C
(12 digits + 1 check digit) C is the check digit to be determined.
1. Multiply all odd digits with 3,
Barcode
7
5
0
1
0
3
1
3
1
1
3
0
Position
E
O
E
O
E
O
E
O
E
O
E
O
3
Multiplier
Result
7
15
3
0
3
3
0
9
3
1
9
3
1
2. Add all the even digits with the multiplied odd digits.
Total sum = 7+15+0+3+0+9+1+9+1+3+3+0 = 51
3
3
3
0
28
3. 51+9 = 60, evenly divisible by 10.
4. So check digit is 9.
5. Final barcode value is 7-501031-311309
2.6.6 Encoding
The process of encoding an EAN-13 barcode is relatively straight forward.
An EAN-13 requires 12-digits of data to be present for encoding while the 13th digit
(the check digit) will be calculated from the data.
a. Total number of bars and modules
An EAN-13 symbol can be divided into two halves, each consisting of six digits
separated by a center guard bar pattern. The whole symbol is surrounded by two
guard bar patterns. The same digit has different encoding depends whether it is in
the left halve or in the right halve. The encoding pattern for digits in the left halve
always starts with a space while the one for digits in the right halve always start
with a bar and ends with a space. An EAN-13 symbol has the following structure:
1. Start guard bars, always with a pattern (bar + space + bar (101)).
2. Left halve, six digits encoded using the encoding from main table A or B.
3. Center guard bars, with a pattern (space + bar + space + bar + space (01010)).
4. Right halve, six digits encoded using the encoding from main table C.
5. Stop guard bars, always with a pattern (bar + space + bar (101)).
Table 2.2: Total number of bars and modules for EAN-13 barcode
Left guards (start)
= 3 bars
= 3 modules
Left hand
= 24 bars
6 x 7 = 42 modules
Center guards
= 5 bars
= 5 modules
Right hand
= 24 bars
6 x 7 = 42 modules
Right guards (stop)
= 3 bars
= 3 modules
Total
= 59 bars
= 97 modules
29
a) Main table of barcode EAN-13 for encoding
This main table indicates how to encode each digit of the barcodes, see table2.3
depending on which half (left or right) of the barcode the digit is found.
Left-Hand
Sets A & B
Right-Hand
Set C
Figure 2.15: EAN-13, left and right hand
Table 2.3: The list of oriented-modules on logic of 0-9 for A, B, C, types
Digit
Left-Hand Encoding
Right-Hand Encoding
Odd Parity Even Parity
Set C
(Set A)
(Set B)
0
0001101
0100111
1110010
1
0011001
0110011
1100110
2
0010011
0011011
1101100
3
0111101
0100001
1000010
4
0100011
0011101
1011100
5
0110001
0111001
1001110
6
0101111
0000101
1010000
7
0111011
0010001
1000100
8
0110111
0001001
1001000
9
0001011
0010111
1110100
Each character has its own code and it is represented using 7 modules. The
corresponding modules are determined from Table 2.3 and Table 2.4. The first digit
will determines the parity encoding of the left hand side characters. Steps for
encoding are given below. Example of encoding an EAN-13 barcode (assume the
check digit is already calculated);
Example: EAN-13 Parity encoding from, see table 2.4, see figure below for barcode
EAN 13
30
Data = 7-612345-67890 (12 digits + 1 check digit), Number System 76, (number
of country), Manufacturer Code 12345, Product Code 67890, Check Digit is 0,
see example barcode divided below.
6 (Value)
= 7 X-dimension bars
= 0101111
= 2 black & 2 white bars
Figure 2.16: Encoding number
Table 2.4: Result for example
Digit name
Numeric Value Encoded with
Binary
-
-
101
2nd Number System
6
Odd
0101111
1st Manufacturer
1
Even
0110011
2nd Manufacturer
2
Odd
0011001
3rd Manufacturer
3
Even
0100001
4th Manufacturer
4
Odd
0100011
5th Manufacturer
5
Even
0111001
Central Guard
-
-
01010
1st Product Code
6
Set C
1010000
2nd Product Code
7
Set C
1000100
3rd Product Code
8
Set C
1001000
4th Product Code
9
Set C
1110100
5th Product Code
0
Set C
1110010
Check Digit
0
Set C
1110010
Right Guard
-
-
101
Left Guard
(always the same)
(always the same)
(always the same)
31
1.
parity digit is ‘7’, thus from Table 2.4, the parity encoding for the six right
hand characters are in the order of Odd-Even-Odd-Even-Odd-Even.
2.
The first of the left hand digits (the second digit of the 13 digit barcode) is 6,
because the parity is odd (obtained from step 1), by referring to Table 2.3,
the digit 6-odd will be encoded as 0101111, and is shown in Figure 2.63.
3.
The second digit is 1, and the parity is even. From Table 2.3, the code for 1 even is 0110011.
4.
The remaining left hand digits are encoded in the same manner.
5.
The right hand digits are encoded directly from Table 2.3.
6.
(Start guard) 101-> (Black, white, black).
7.
(Six left digits) 0101111-> (white, black white, black, black, black, black),
0110011 –> (White, black, black, white, white, black, black) etc, 0011001,
0100001, 0100011, 0111001.
8.
(center guard) -01010 -> (White, black, white, black, white).
9.
(six right digits) 1000010 ->(Black, white, white, white, white, black, white)
etc, 1100110, 1100110, 1000010, 1110010, 1110100
10.
(end guard) -101-> (Black, white, black).
2.6.7 Decoding
Decoding is just the reverse of the encoding process. By comparing the bars
with Table 2.3, the corresponding digit value and its parity can be determined. The
parity of the six left hand characters will decide the first character of the barcode.
When all the digits are obtained, the check digit can be calculated and then compared
with the check digit obtained from scanning. If the check digits do match, the
barcode is verified and assumed to be correct.
CHAPTER 3
METHODOLOGY
3.1 Introduction
This chapter describes the overall steps needed to decode an image barcode
with a camera built in the PDA system. Detailed information on how each step is
implemented is given, several methods are presented on each step.
3.2 Barcode Image Devices
The imaging barcode system should produce barcodes with high quality so
that the desired objects can be extracted successfully for processing.
The task of the system is to read EAN-13 barcode using a PDA with a buildin camera or reading from a file. In this case, a barcode image is captured using a
PDA and then decode it, see Figure 3.1, once captured the PDA will search for the
barcode area.
33
Figure 3.1: Architectural Overview: EAN-13 barcode and resolution system consists
of a PDA using camera and load from file application for decodes barcode.
3.3 Image Capturing
In this Project a SD camera is used (HP photosmart mobile camera). The
system can also read image from a file, see figure 2.3.
Press to
test to
load
from
file
barcode
Figure 3.2: There are some progresses used to read barcode
34
3.4 Barcode processing in PDA
There are some aspects that need to be mentioned when designing a barcode
reader. This design has two parts to a read barcode image. First-part, the capture
barcode image by camera built-in PDA (online). Second-part, load from file
(offline). This barcode image can contain whole a barcode or a partial barcode
depending on the field of view. See figure below.
Figure 3.3: Image processing in PDA
35
3.4.1 Searching for barcode image automatically
When the system wants to read a barcode it gives the coordinate of the
barcode to the barcode reader, see figure 3.4, some symbols barcode image. Then,
searching for the image barcode automatically (locate the area of interest), see figure
3.4. The barcode localization algorithm will then be applied to the barcode image.
Figure 3.4: Some symbols barcode image
To be able to identify the elements of a barcode with good result, the location
of interest of the barcode must be known. This area will be referred to as “the region
of interest” see figure above. There are scenarios after a barcode image has been
searched automatically. Thereby, it gets an accurate result when identifying the
elements. The localization algorithm will give information about the extent of the
barcode outside the image.
The system will be instructed to grab new a barcode images at the new
positions. Therefore, the localization algorithm must be able to locate the barcode
image area for any orientation of the barcode. Thus, to be able to identify where the
barcode is in an image one must be able to specify what is special about a barcode
area, either in the spatial domain. Linear barcodes have thin and narrow parallel lines
36
and these lines have high contrast. Two-dimensional symbols also have high
contrast, but they do not contain parallel lines.
In most barcode applications, the barcode occupies a small part of the
barcode image. In this application, the code will most likely occupy a large part of
the image, because the image size is small compared to the barcode. The direction of
the barcode is not known in most cases. The algorithm must therefore be able to
locate a barcode area in any orientation.
3.4.2 Identification of the Bars and Spaces
To be able to decode the barcode, the width of the elements must be
identified with high precision. One way to get a waveform for analysis is to use the
intensity in the barcode image in a similar way as the voltage from a laser scanner.
To accomplish this accurately the orientation of the barcode must be known.
Two adjacent edges in the waveform constitute the start and stop of an element. So,
the task is to detect the edges of the waveform. If the image barcode is damaged it
might have to be filtered to improve reading performance.
3.4.3 Estimating How Correctly the Elements Have Been Identified
All barcode symbols have a well defined set of valid element widths. For
EAN-13 (X-XXXXXX-XXXXXX), the set is {X, 2X, 3X, 4X, 5X, 6X}, X is the
smallest element size. If the output from the identification of the bars and spaces is
not within these sets or matches the elements in these sets poorly, an alternative
method should be used for identifying the bars and spaces.
37
3.4.4 Decoding the Barcode
The proposed decoding is as follows:
•
First, it obtains a sample row across the barcode image.
•
The signal is then converted into the binary form by simple thresholding
based on the mean value of the signal. The signal in a binary form, which is
essentially a binary sequence of 1’s and 0’s.
•
The run-length encoding is performed on the binary sequence so, that the
individual width of the alternating black and white bars can be determined.
•
The next step is to determine where the barcode begins by searching for the
left hand guard pattern.
•
Once the left hand guard pattern is found, the decoder will read the next 6
sets of 4 bars to determine the values of the 2nd, 3rd, 4th, 5th, 6th and 7th
barcode digits.
The center guard pattern should be detected before reading the next 6 sets of
4 bars, which specify the values of the 8th, 9th, 10th, 11th, 12th and 13th digits. The
lock-up tables for the EAN-13 symbologies are given in table 3.1 and table 3.2.
Table 3.1 is the lock-up table for a regular barcode and table 3.2 is for a flipped or
mirrored barcode. The decoding algorithms were used, namely the Predictive
decoding algorithm [1].
Digit
0
1
2
3
4
5
6
7
8
9
Table 3.1: Normal barcode (left to right)
Left
Right
Odd
Even
Odd
0001101
3211
0100111
1123
1110010
0011001
2221
0110011
1222
1100110
0010011
2122
0011011
2212
1101100
0111101
1411
0100001
1411
1000010
0100011
1132
0011101
2311
1011100
0110001
1231
0111001
1321
1001110
0101111
1114
0000101
4111
1010000
0111011
1312
0010001
2131
1000100
0110111
1213
0001001
3121
1001000
0001011
3112
0010111
2113
1110100
3211
2221
2122
1411
1132
1231
1114
1312
1213
3112
38
Table 3.2 Flipped or mirrored barcode
Digit Left (inverted)
Right (inverted)
Even
Even
Odd
0
1011000
1123
1110010
1123
0100111
1
1001100
1222
1100110
1222
0110011
2
1100100
2212
1101100
2212
0011011
3
1011110
1411
1000010
1411
0100001
4
1100010
2311
1001110
2311
0011101
5
1000110
1321
1001110
1321
0111001
6
1111010
4111
1010000
4111
0000101
7
1101110
2131
1000100
2131
0010001
8
1110110
3121
1001000
3121
0001001
9
1101000
2113
1110100
2113
0010111
3211
2221
2122
1411
1132
1231
1114
1312
1213
3112
a. Predictive Decoding
One of the major advantages of predictive decoding is that it handles noise
and inaccuracies very well. The predictive method basically predicts the outcome
without comparing all the bars. The basis of this method is that, certain
combinations of bars are unique and thus allowing some optimization to be
performed. In a worst case scenario, the predictive decoding method only
requires 3 out of 4 bars to be present for successful decoding.
3.5 Pre-Processing
As in all applications involving image acquisition followed by processing of
the images, the qualities of the images are of great importance. Many things do
influence the output of the camera built-in PDA, and as regarding all photography,
the lighting is the foremost important variable which affects it. Motion of the object,
and the distance between the camera and the object are other important issues.
Most of which depends on the actual location of the object and its light
conditions, or the chosen camera built-in PDA and its features and performance.
However, in many applications the sought image is not only an image that is
appealing to the human eye. Other features might be important to amplify or reduce
to enhance the relevant information of the image.
39
3.5.1 The RGB color model
In the RGB model, each color appears in its primary spectral components of
red, green and blue. This model is based on a Cartesian coordinate system. The color
subspace of interest is the cube shown in figure 3.5. In which RGB values are at
three corners, cyan, magnets and yellow are three other corners, black is at the origin,
and white is at the corner father from the origin. In this model, the gray scale (point
of equal RGB values) extends from black to white along the line joining these two
points. The different colors in this model are points on or inside the cube, and are
defined by vectors extending from the origin. For convenience, the assumption is that
all color values have been normalized so, that the cube shown in figure 3.5 is the unit
cube. That is, all values of R, G, and B are assumed to be in the range (0, 1).
Image represented in the RGB color model consist of three component
images, one for each primary color. When fed into an RGB monition, these three
images combine on the phosphor screen to produce a composite color image. The
number of bits used to represent each pixel in RGB space is called the pixel depth.
Consider an RGB image in which each of the red, green, and blue images is an 8-bit
image. Under these conditions each RGB color pixel (that is, a triplet number of bits
per plane). The full color image is used often to denote a 24-bit RGB color image.
B
Blue
0, 0, 1
Cyan
Magenta
White
Gray
scale
0, 1, 0
Green
Black
1, 0, 0
R
Red
Yellow
Figure 3.5: Schematic of the RGB color cube
G
40
3.5.2 Gray scaling
Gray scaling is done to remove the color values of the image. It is a very
common preprocessing step in most image processing applications where additional
color information is unnecessary. A color image is a composition of 3 separate layers
of Red, Green and Blue. Processing on a color image is 3 times slower as the
processing has to be performed on three different layers. Besides that, a color image
also requires three times the memory space compared to a gray level image (for an
uncompressed image). These drawbacks are definitely undesirable for real-time
application especially when the color information in not required. Grayscaling
converts a color image (a 24-bit RGB, 8-bit per channel in this case) to an 8-bit gray
level image, thus representing the light intensity of the image, see Figures below.
Thereby, the data is ready for further processing.
R
G
B
Figure 3.6: Illustrating difference between a general RGB color image and a general
gray scale image.
Figure 3.7: Original gray-scale image
41
3.5.3 Image Enhancement
To prepare the image for the next stage in the system, the Feature Extraction
stage, it has to be suitably enhanced. This process is a prelude to the Barcode
Localization phase, which is the first thing done in the Feature Extraction stage. In
this case barcodes are the region of interest, thus making the process of high- lighting
the patterns that are characteristic for barcodes the aim of this section. This means
that areas of high contrast containing many parallel lines are considered highly
interesting, and should thus be amplified. While oppositely, areas of uniform grayscale levels are considered as of low interest regarding barcodes.
The basic idea is to sharpen the image, thereby making details and edges
appear clearer, and at the same time to suppress areas of low interest, such as fields
of uniform gray-scale etcetera. Intuitively averaging of pixels in a region – which is
analogous to integrating over that region - does blur detail. Leading to the
expectation that differentiation yields the opposite effect, thus sharpening the image;
which is just the sought-for effect.
As a collective name these kinds of operators are called derivative filters, and
the most common method to achieve it is by using the gradient. The analytical
expression for the gradient, of the function f(x; y), this step is carried out to enhance
certain details in the image such as edges or to attenuate others such as noise.
Brightness and contrast of the image can also be adjusted here. Three filters can be
applied consecutively in a cascading manner to the image in addition to brightness
and contrast adjustment. Specifically, there are four spatial filters available for use,
mainly for sharpening and blurring. The filters are applied automatically. The filters
that are available and their respective kernels are shown in Figure 3.9
A convenient way of doing this kind of processing on images is by letting a
windowing function operate on the image. The windowing function exemplifed with
a window of 3 x 3 pixels works as follows: Consider Figure 3.7, where the z-values
represent the gray-level values of the original image. The values of all the nine
pixels, z1 through z9, are each multiplied with pre-defined factors. Then the sums of
all components are set as the new centre of the window, in this case position z5. [2]
42
The window is then moved on to the next pixel, and the same procedure is repeated,
see figure 3.8. By sliding the window in an overlapping fashion the whole image,
except the pixels in the margin of the image.
Figure 3.8: A 3x3 window, for use in a windowing function, where the z-values
corresponds to the gray-scale values of the original image.
Figure 3.9: Spatial filters (a) Gaussian Blur, (b)Laplacian (c) Sharpen
(d) Unsharpen Mask
3.6 Scanning Direction
The first step is to scan for a barcode or multiple barcodes in the scene or
image (a frame in the case of real-time acquiring). The method employed is similar
to that of a laser scanner. Image is scanned in 4 directions, horizontally (left to right),
vertically (top to bottom), 45 degrees diagonally (top left to bottom right) and -45
degrees (bottom left to top right), shown in Figure 3.10 Each of the direction is
known as a scan direction. The number of scan line depends on the scanning
resolution set by the user. Depending on the accuracy required, the number of scan
lines can be increased or decreased [1].
43
Figure 3.10: Scan 4 directions implemented
Each direction detects flipped and mirrored barcodes without a second pass.
This is because; flipped and mirrored barcodes are handled by the decoding
mechanism rather than the scanning mechanism. The scanning mechanism is merely
for obtaining a provisional location of a barcode.
(a)
(b)
(c)
(d)
Figure 3.11: These are some direction of a barcode at different angles, (a)
Horizontal (b). Vertical (c) Diagonal (d) invest horizontal
Four scan directions are implemented to allow detection of rotated barcodes
(rotation of barcodes also referred as skewing) which is a usual occurrence in reality.
By scanning horizontally (0), vertically (180) and diagonally (-45 and 45), the
barcode reader is capable of detecting barcodes throughout the 360o range. See
figure 3.11
44
Angular information of the barcode is acquired through knowledge of the
vector displacement, k, and the distance, d, between the correlated vectors, when the
correlation between two vectors is calculated. The barcode's angle is derived as (µ =
arctan( d k )), see Figure 3.12 Angles in the images are defined as increasing
counterclockwise from the x-axis, with 90 degrees on the y-axis, and 180 degrees on
the negative x-axis
Figure 3.12: Illustrating how the barcode's angle µ is derived using the vector
displacement, k, the distance d between two vectors, and basic trigonometry.
3.7 Barcode Identification & Extraction
One-dimensional barcodes are made of bars and spaces. This distinct feature
is what the scanning process is looking for. The identification and extraction of the
EAN-13 barcode consist of 4 main steps. Referring to Figure 3.12, the steps are;
Figure 3.13: Steps to identify and extract the EAN-13 barcodes
45
3.8 Program Architecture
3.8.1 Overview of Programming Languages Used For PDA Platform
There are many languages that can be used to program PDA's with Windows
CE, OS or Windows Mobile 2003 or 2005, but the most common and popular are:
a. Microsoft Visual Studio 2005 Professional Edition
Embedded version of Visual C++, C#, J# and Visual Basic are included in Visual
Studio 2005 Professional Edition C++. It also contains several SDK tools like
Remote Registry Editor, Remote Spy++, etc. More than 95% of Pocket PC
developers use this package.
b. Visual CE
Visual CE used for building database applications for Windows CE. It uses drag
and drop controls to create an electronic form. ODBC-enabled software has been
used to upload, download, or update the data of windows CE device.
c. NS Basic/CE
NS Basic is a complete development environment enabling the development of
applications with a Pocket PC look. NS Basic includes features such as
databases, serial and IR communications, signature capture. Development takes
place on the desktop or on the device itself.
d. Pocket PC
Pocket PC does not generate machine code like Visual C++. Instead, it written
intermediate code interpreted by a freely distributable runtime. Windows CE
machines are particularly well suited to the use of VMs because they tend to run
client applications that don't need incredibly fast loop or integer performance. In
addition, Windows CE powered devices can have many different set of CPUs and
platforms. Instead of producing a separate executable for each platform and each
CPU, Pocket PC allows to distribute one binary for all Windows CE devices.
46
e. Waba
Waba is a free open source programming platform that lets developers written a
program which can run both on Windows Powered and Palm devices. A version
for Compaq iPAQ Pocket PC is an available.
f. CASL
CASL is an easy to use Windows integrated development environment, and a full
featured scripting language, variables, objects, and functions provided by the
CASL language and create powerful and flexible applications.
3.8.2 Program Build on PDA
This project does some server processes is written by visual Studio 2005 c++
(see Appendix A and Appendix B), is made of some main classes, see table below.
Table 3.3: These are classes used in program
This class encapsulates image processing routines to be
Image
performed on a 32-bit RGBA image in memory (device
context).
Data
Decode
EAN
Barcode
Module
Handles global program variables
Contains scanning and decoding functions for EAN-13
A class to hold all barcode parameters such as height,
width, digit, coordinate, etc
Holds module parameters such as height, width, normalized
width, color, etc. (referred by Barcode)
SDIOCam Camera SDIO SDK Specification
47
3.9 Program screenshot
The program utilizes one user thread and one image processing thread.
Threading allows maximum flexibility and efficiency. Threading allows certain
portions of program code to be executed separately but in parallel to other executing
codes. Thus, the application is also known as a multi-threaded application.
This program used a multi-threaded applications provide better performance
on multi processor systems onto some button. Threading also opens up the possibility
of parallel execution of codes that do not depend on each other, thus avoiding any
waiting that typically occurs in sequential programs. Execution of dependent code
can also be implemented using threads, with certain locking and unlocking
mechanisms in place.
3.9.1 Program interface
This is program interface, can be from here use offline to a read barcode see
figure below.
11
1
3
2
4
6
5
8
7
9
Figure 3.14: program interface
10
48
The user interface consists of several important elements which are;
1-
Display screen.
2-
Refresh, use to resume camera.
3-
Snapshot, input image capture size 320 x 240 up pixels from camera
then, converts from JPEG to BMP, after that, saves in PDA BMP
then, display on screen and analysis it.
4–
Auto, this button used on catch image and analyses (online) without
save in PDA.
5-
Test, Load image barcode from file into the test program (offline).
6-
Exit.
7-
Predictive, Decoding algorithm selection, Predictive
8-
Beep; Enable Beep, (when barcode is detected) and/or Multiple
Barcode Detection.
9-
Decoded barcode value display.
10 -
Consume scan operation by milliseconds.
11-
Border is drawn around the barcode expanse
3.9.2 Using the HP Photosmart Mobile Camera
This a camera will use in a program in real-time (online) with PDA
Figure 3.15: Getting Acquainted
49
Table 3.4: specification for interface camera
Component
Function
X. Lens
Shows what will be seen in the photo.
Y. Rotating
Allows to turn the lens to aim at the subject when
Lens Body
composing a shot.
Z. SDIO
Interface between iPAQ pocket PC and Photosmart
interface
Mobile Camera.
`
CHAPTER 4
RESULT
4.1 Introduction
This chapter shows the results of the system when tested with actual barcodes
in real-time (online) and load from file (offline). The experiments are to test the
system’s capability, accuracy and performance are described based when subjected
to various objects with different properties and in different conditions. Tests were
also carried out with rotated barcodes and barcodes residing on various surfaces.
Finally, this chapter shows the performance comparison with existing vision based
barcode readers.
4.2 Uneven Resolution, Shadow, Shake and Illumination
One of the major concerns is the level of resolution. Poor lighting and
shaking or incorrect camera position may cause shadowing and uneven illumination
to be present, see figures 4.1. Although in industrial applications (such as on a PCB
manufacturing line) the presence of uneven illumination in unlikely (due to strict
lighting and a controlled production environment), this cannot be said in situations
where the device is handled by human or when there is human involvement.
51
(a)
(b)
(c)
(d)
Figure 4.1: These are some samples for barcodes image are not clear, all of them
(uneven resolution and shake).
4.3 Tests of Barcode Orientation
1. Firstly, the capture barcode image must be very clear, that means the bars
and space are very clear, see figure below.
(a)
(b)
Figure 4.2: Some types of barcode all of them very clear
2. Secondly, if the captured barcode images are bad, can not analyze
because bars and spaces are not clear, that mean of barcode has some blur
or resolution is bad or shake in barcode image see figure
Figure 4.3: Some types of barcode all of them not clear
52
4.3.1 Computing the orientation of the barcode
Computing the orientation of the barcode is important for accurate
classification of the bars and spaces. The orientation can either be determined from
the bars themselves or from the area of interest, i.e. the output from the localization
algorithm.
a. Computing the orientation of the Bars
The orientation of a bar code can be computed from the direction of the bars.
To get an accurate result, some smoothing of the input image is required. This
method can be applied to the entire bar code region.
b. Analyzing the Output from the Bar Code Localization Algorithm
By analyzing the output from the algorithm for detecting the region of
interest, a good result on the barcode angle can be achieved. All barcode are
symbols rectangular shape. The region of interest for a barcode can be
estimated by the shape of a rectangle (Angle = α = 90 − β), see figure 4.4
(a)
(b)
Figure 4.4: Shows the output from the localization algorithm. Angle α is the
angle of the bar code. The angle is also given by 90 - β
There is one problem with this approach. If the area of the barcode
region is too small, the estimated angle may be highly sensitive to inaccurate
estimations of the barcode region. If small regions of interests are merged to
one large region the angle can be estimated more accurately.
X = x. cos(θ ) − y.sin (θ ) − m. cos(theta ) + n.sin (θ ) + m
Y = y. cos(θ ) + x.sin (θ ) − m.sin(theta ) − n.sin (θ ) + n
53
Figure 4.5: Rotation
4.4 Show scan diagonal read rotated barcodes (offline)
The ability of the developed program to read barcodes on irregular surface is
shown in figure 4.6
The detection barcode value is printed at the bottom of the screen and a
border is drawn around the barcode region. Its successful detection on the remaining
surface is mentioned earlier.
(a)
(b)
(c)
Figure 4.6: Diagonal (+45, - 45), (a) scan consume operation 393ms,(b) scan
consume 1482ms, (c) scan consume operation 617ms.
54
4.5 Show scan horizontal read rotated barcodes (offline)
The capability of the developed program to read barcodes on flat surface is
shown in figure 4.7
The detection barcode value is printed at the bottom of the screen and a
border is drawn around the barcode region. Its successful detection on the remaining
surface is mentioned earlier.
(a)
(b)
(c)
Figure 4.7: Horizontal, (a) scan consume operation 531ms,(b) scan consume 492ms,
(c) scan consume operation 462ms.
4.6 Show scan vertical read rotated barcodes (offline)
The capability of the developed program to read barcodes is along the axis of
cylinders and irregular surface shown in figure 4.8.
The detection barcode value is printed at the bottom of the screen and a
border is drawn around the barcode region. Its successful detection on the remaining
surface is mentioned earlier.
55
(a)
(b)
(c)
Figure 4.8: Vertical, (a) scan consume operation 435ms,(b) scan consume 336ms, (c)
scan consume operation 515ms.
4.7 Show scan horizontal read rotated barcodes (online)
This section shows the scanning process using mobile camera (online) of the
developed program to read barcodes on flat surface as shown in figure 4.9
The detection barcode value is printed at the bottom of the screen and a
border is drawn around the barcode region. Its successful detection on the remaining
surface is mentioned earlier.
(a)
(b)
(c)
Figure 4.9: Some tests from camera (online), (a) scan consume operation 203ms,(b)
scan consume 270ms, (c) scan consume operation 272ms.
56
4.8 Time Consumption
This is an important property indicating the performance of the system is time
consumption. For measures concerning time to be relevant the hardware and
software configuration of the system. In this application all testing and processing
were executed on a PDA:
Hardware
- Intel 624MHz, PXA 270 processor
- 135 MB user available memory.
Software
- Windows CE 3.0
- Visual Studio 2005, C++.
The time consumption measured without the graphical interface illustrates the
actual time consumption of the algorithm - with the above defined hardware and
software. When images of different levels of resolution were tested from file or from
camera onto the differences in time consumption, therefore, the result became
consumptions different.
4.9 Performance Comparison
Real-time (online) and load from file (offline) processing leads to strict time
constraints. The faster the processing the better it is. The processing time largely
depends on the size of barcode image (height x Width), resolution of barcode image
from camera, shake of camera and the computing power (PDA hardware). The
smaller image usually fast in the computing. Moreover, using a faster Pocket PC will
definitely produce closer results and will bring the system to be as real-time as
possible. The program will repeat the same code over and over again thus it is
important that the algorithms be as efficient as possible. In the program developed,
the processing time is determined by the following factors:
1. The size of the frame (smaller means faster).
57
2. The implementation algorithm of image enchantment (grayscale, filters add
to computation time )
3. Number of scan barcode image and scan resolution (that means higher
resolution).
4. Predictive decoding (the latter is slower).
The average decoding time is calculated based on the time taken to
successfully detect and decode all of images shown in Appendix B. In the case of
incorrect detection or failure of detection, the sample is omitted. The total time is
obtained by summing up the time taken for all successful detections and it is
normalized with the number of pixels processed, see figure below.
COMPARE
Shake
Resolution
Load from file (offline)
Camera (online)
0
20
40
60
Figure 4.10: compare consume operation
80
100
CHAPTER 5
CONCLUSION
5.1 Conclusion
The program can capture images from offline windows bitmap (BMP) files or
in real-time from a camera that is attached or either built in the PDA. This image
obtains barcode which is used for
further decoding. Thereby, software is already
designed based on PDA platform by which different barcodes can be read &
decoded.
5.2 Recommendations for Future Work
The program can be improved by sending data to server using wireless
technology. To read image barcode, this program can be used in smart phones. And,
with additional software, this technique can be used in hospitals supermarkets, etc,
after updating the database or connecting it with the server.
More symbologies can further be added, however, program developed can be
migrated to run on other devices to open up the possibilities for the users to obtain
product information just by snapping a picture of the image barcode.
59
REFERENCE
1. Usman Ullah Sheikh, Real–time barcode reader using active vision ,It is to
decode the UPC-A and EAN-13 barcodes using an active vision system the
system was implemented in C++ ,UTM,2004.
2. Johan Bylund, Fredrik Jirhede, Visual Barcode Reading, the implementation
of a system for visual barcode EAN-13 reading, using a network camera, the
system was implemented in C++, Royal Institute of Technology (KTH) in
Stockholm, Sweden., 2003
3. Peter Sundström, Barcode EAN-13 Reader for Surface Mounting Systems,
reading bar codes with a camera that has a field of view that is smaller than
the size of the bar code: 760326-0451 2001.
4. N. Normand, C. Viard-Gaudin . A Two-Dimensional BarCode Reader.
Laboratoire Analvse et Traitement des Images (LATVSEI) IRESTE - Route
de Gacheti CP 3003 - 44087 NANTES CEDEX 03; France , 1994.
5. Xi-Ping Luo, Li-Xin Zhen, Gang Peng, Jun Li, Bai-Hua Xiao Motorola
China Research Center, Shanghai, P.R.China, and Camera based mixedlingual card reader for mobile device: IEEE, 2005.
6. Eisaku Ohbuchi, Hiroshi Hanaizumi† , Lim Ah Hock‡, Barcode Readers
using the Camera Device in Mobile Phones: IEEE, 2004.
7. Hisayuki Tatsumi1), Yasuyuki Murai2), Masahiro Miyakawa1) and Shinji
Tokumasu2), Providing Environmental Information by Data Carrier +
Networks : Tsukuba College of Technology.
60
8. H. Kato, K. T. Tan, 2D Barcode for mobile phones. The difference between
traditional 1D barcodes and 2D barcodes for camera-enabled cell phone
application: Edith Cowan University, Western Australia, 2005.
9. Wesley Chan, Project Voyager: Building an Internet Presence for People,
Places, and Things, The Voyager Personal Shopping Assistant (PSA)
connects shoppers in a supermarket to virtual services, linked to specific
products: MASSACHUSETTS INSTITUTE OF TECHNOLOGY, 2001.
10. Robert Adelmann, Marc Langheinrich, Christian Flörkemeier, Toolkit for
Bar Code Recognition and Resolving on Camera Phones – Jump Starting the
Internet of Things: Institute for Pervasive Computing, ETH Zurich.
11. I, Hong-Yuan &om, Liang-Hua ChenB, Hsiao-Rong Tana, and Jun-Wei
Hsiehm , A-BASED BAR CODE RECOGNITION SYSTEM USING
NEURAL NET: IEEE, 1993.
12. Jeffrey Adair, Locating, Tracking, and Interpreting Ean-13 Bar Code
Waveforms in a Two-Dimensional Video Stream : Hiram College, 2001.
13. Douglas Chai and Florian Hock , Locating and Decoding EAN-13 Barcodes
from Images Captured by Digital Cameras : Visual Information Processing
Research Group School of Engineering and Mathematics Edith Cowan
University, IEEE, 2005.
14. Aparna Rajan Ramchandran , A HANDHELD PDA USING RFID TAGS
FOR CHILD VISITORS TO THE MICHIGAN 4-H CHILDREN'S
GARDEN : Michigan State University , 2004.
15. Elsag S.p.A. Italy, Datalogic S.p.A. Italy, A COMMON IMAGE
PROCESSING FRAMEWORK FOR 2D BARCODE READING.: IEE,1999.
61
16. Yasser Ebrahim, Wegdan Abdelsalam , Maher Ahmed, Siu-Cheung Chau,
Proposing a Hybrid Tag-Camera-Based Identification and Navigation Aid
for the Visually Impaired: IEEE, 2004.
17. Kwang Bok Lee and Roger A. Grice, The Embedded Zooming Applications
for Personal Digital Assistants (PDA) : Troy, New York, USA, 0-7803-7949 ,
IEEE, 2003.
18. Eva Brandt, Erling Bj ِrgvinsson and Per-Anders Hillgren, PDA´s, Barcodes
and Video-films for Continuous Learning at an Intensive Care Unit.
NordiCHI, October 19-23, 2002.
19. Hee II Hahn Joung Koo Joung, Implementation of algorithm to decode twodimensional barcode PDF-417: 0-7803-7488 IEEE, 2002.
20. Yonghoon Choi¹, Jong Un Won¹, and Jong Heung Park, An Experimental
Testbed for Parcel Handling with RFID Technology: 305-358, Republic of
Korea, Feb 2006.
21. Klaus-Werner J.RG, Torsten Gattung & Joachim Weber, Supporting Mobile
Robot Localization by Visual barcode Recognition : Kaiserslautern
University, Santa Barbara, California, USA, October, 1999.
22. Johan Bylund and Fredrik Jirhede, Vision Barcode Reading : Royal Institute
of Technology (KTH) in Stockholm, Sweden, Dec 2003.
23. Lynn Ltd., 912 North Main Street, Ann Arbor, MI 48104 313-9961777(v),663-7937(fax) http://www.adams1.com/pub/russadam/stack.html (3di)
24. N. Ohboshi, R. Nadayoshi, Y. Mitomi, T. Kuroda, N. Sakihana, T.
Tachibana, Y. Miyachi, H. Yoshihara: "A Study of Electronic Treatment
Planning System for Pressure Ulcers using Personal Digital Assistant",
Journal of JAMI, Vol.24, No.1, pp.99-109,2004.(Japanese)
62
http://www.kuhp.kyoto-u.ac.jp/~mi/research/wearable/index_en.shtml
25. Barcode reader with smartphone , 2005
http://www.symbianone.com/content/view/3025/31/
26. Barcode basic, barcode software center
http://www.mecsw.com/specs/speclist.html
27. BarCodeWiz Barcode ActiveX Control,
http://www.barcodewiz.com/barcodeactivexhelp/uccean128.asp
28. ActiceBarcode, http://www.activebarcode.com/codes/ean13.html,
http://www.gs1india.org/ABOUT/his88-92.htm.
29. .EAN-13 BACKGROUND INFORMATION, http://www.barcodeisland.com
30. Richard E Woods, Digital Image Processing (Second Edition), University of
Tenness.
63
APPENDIX A
Camera SDIO SDK Specification
SDK Interface
1. BOOL SDIOCamVersion(HANDLE hCom, TCHAR *DriverVersion)
Description:
Get driver version information
Params
hCom : Camera Device Handle
DriverVersion : buffer to receive data
Return Value
Zero if fail,otherwise not zero;
2. BOOL SDIOCamData(HANDLE hCom, UCHAR *ScreenBufShow,
DWORD *ll)
Description:
Get frame data from driver
Params
hCom : Camera Device Handle
ScreenBufShow : Buffer to receive frame data
ll : To receive data length
Return value
Zero if fail,otherwise not zero;
64
3. BOOL SDIOCamInit(HANDLE hCom, HWND Mainhwnd )
Description
Device initialization
Params
hCom : Camera Device Handle
Mainhwnd : Handle of Application main window
Return value
Zero if fail,otherwise not zero;
4. BOOL SDIOCamSnapShot(HANDLE hCom, TSNAPINFO snapshotinfo)
Description
Request for doing snap shot
Params
hCom : Camera Device Handle
snapshotinfo : Image quality to achieve and file name、 directory information,
resolution and more…
Return Value
Zero if fail,otherwise not zero;
5. BOOL SDIOCamPreviewStart(HANDLE hCom, HWND hwVideo,
int prvmode)
Description
Request for starting preview
Params
hCom : Camera Device Handle
hwVideo : Handle of Video window
prvmode : preview mode, values:
PREVIEW_160_120_1X : preview with 160*120 and zoom 1x
PREVIEW_160_120_2X : preview with 160 *120 and zoom
2x
65
PREVIEW_160_120_4X: preview with 160 *120 and zoom
4x
PREVIEW_320_240_1X: preview with 320*240 and zoom
1x
PREVIEW_320_240_2X: preview with 320*240 and zoom
2x
PREVIEW_320_240_4X: preview with 320*240 and zoom
4x
Return value
Zero if fail,otherwise not zero;
6. BOOL SDIOCamPreviewStop(HANDLE hCom)
Description
Request for stopping preview
Params
hCom : Camera Device Handle
Return value
Zero if fail,otherwise not zero;
7. BOOL SDIOCamPowerOff(HANDLE hCom)
Description
Request for shutting down the power of camera
Params
hCom : Camera Device Handle
Return value
Zero if fail,otherwise not zero;
8. BOOL SDIOCamSetting(HANDLE hCom,_PARAMETERINFO parainfo)
Description
request for Setting the mode of video or snapshot picture
Params
hCom : Camera Device Handle
66
Parainfo : Mode information to be set
Return value
Zero if fail,otherwise not zero;
9. void SDIOCamPreviewInit( void )
Description
Initialize to preview
Params
NULL
Return value
No return value;
10. BOOL SDIOCamDeCode( int PreMode, UCHAR *inBuf, UCHAR
*outBuf, ULONG dataLenLeft)
Description
Decode Image data from JPEG formate to BMP format Params
PreMode: Preview Mode.( as SDIOCamPreviewStart)
InBuf : Buffer of JPEG data source to decode
OutBuf : Buffer to receive decoded BMP data.
DataLenLeft : Data length of JPEG data source
Return value
Zero if fail,otherwise not zero;
z
Structures Definition Needed
1．
typedef struct imgcolor_struct {
UCHAR avRed;
UCHAR avGreen;
UCHAR avBlue;
UCHAR avY;
}Imagecolor;
67
Description
This structure defines the color information
Members
avRed : Value of red
avGreen : Value of green
avBlue :Value of blue
avY : Brightness
2. typedef struct _TSNAPINFO {UCHAR resolution;UCHAR quality;
TCHAR filename[100];}
int inbufferlen;
unsigned char *imgbuff;
int *outbufferlen;
HINSTANCE hinst;
} TSNAPINFO, *PTSNAPINFO;
Description
This structure defines the information of snapshot picture when
requesting for do snapshot
Members
resolution : resolution of snapshot picture. Values:
TAKPIC_1280_1024:
1280 *1024 wiht zoom 1x
TAKPIC_1280_960:
1280 *960 wiht zoom 1x
TAKPIC_640_480: 640 *480 wiht zoom 1x
TAKPIC_320_240: 320*240 with zoom 1x
TAKPIC_640_480_2X:
640 *480 wiht zoom 2x
TAKPIC_320_240_2X: 320 *240 wiht zoom 2x
TAKPIC_320_240_4X: 320*240 with zoom 4x
quality : quality of snapshot picture. 0 : good 1: better 2: best
filename : file name of picture to save(full name, directory inside).
inbufferlen:
imgbuff:
outbufferlen:
hinst:
68
3. typedef struct{
int WhiteBalance;
int Color;
int Compression;
int AeMetering;
}_PARAMETERINFO, *_pPARAMETERINFO;
Description
This structure defines the information of snapshot picture when do
setting
Members
WhiteBalance : Mode of whitebalance. Values:
WB_AUTO: auto;
WB_SUN: sun;
WB_TUNGSTEN: tungsten;
WB_FLUORESCENT: fluorescent;
Color : Color of picture, (0: full color; 1: black & white; 2: negative;
3: negative; 4: cool )
Compression : Compression of picture ,( 0: good; 1: better; 2: best )
AeMetering : AeMetering of picture,( 0: average; 1: center-weighted;
2:spot)
z
Preview Mode and Snapshot resolution values
For Snapshot:
Zoom*1:
#define
TAKPIC_1280_1024
0
//1280 *1024 wiht 1x
#define
TAKPIC_1280_960
1
//1280 *960 wiht 1x
#define
TAKPIC_640_480
2
#define
TAKPIC_320_240
4 // 320*240 with 1x
#define
TAKPIC_640_480_2X
7
//640 *480 wiht 2x
#define
TAKPIC_320_240_2X
8
//320 *240 wiht 2x
//640 *480 wiht 1x
Zoom*2:
69
Zoom*4:
#define
TAKPIC_320_240_4X
17 // 320*240 with 4x
For Preview:
#define
PREVIEW_160_120_1X
6
//preview with 160*120 and
PREVIEW_160_120_2X
20 //preview with 160 *120 and
PREVIEW_160_120_4X
21 //preview with 160 *120 and
#define
PREVIEW_320_240_1X
4 // 320*240 with zoom 1x
#define
PREVIEW_320_240_2X
9 //preview with 320*240 and
PREVIEW_320_240_4X
17 // 320*240 with zoom 4x
zoom 1x
#define
zoom 2x
#define
zoom 4x
zoom 2x
#define
z
White balance values
#define WB_AUTO
0
//auto
#define WB_SUN
1
//sun
#define WB_TUNGSTEN
2
//tungsten
#define WB_FLUORESCENT 3 //fluorescent
All above need SDIOCam.h 、 SDIOCam.lib 、 SDIOCam.dll
70
APPENDIX B
Visual Studio 2005 C++ CLASS DECLARATION
Image Processing Class Library Reference
1. RTBCRwithPDADlg.cpp
All procedures in program will be done it and all of classce, operatore grayscale
and lowpass filter on start vidoe and used thread to some button.
volatile bool fThread;
UINT __cdecl MyThread( LPVOID pParam )
{
CRTBCRwithPDADlg *dlg = (CRTBCRwithPDADlg*) pParam;
while(fThread)
{
if (SDIOCamData(hCom,ScreenBufShow,&ll))
if(SDIOCamDeCode(gPreMode,ScreenBufShow,ScreenBuf24,ll))
dlg->Capture();
•
To Load a barcode image from file (offline).in PDA
CString strFilter = L"Bitmap Files (*.bmp)|*.bmp|All Files (*.*)
|*.*||";
•
Display a size for screen.on PDA (can use any size).
71
pdc->StretchBlt(2,0,320,240,&hdcMem,0,0,280,180,SRCCOPY);
•
This is use, convert from jpg to bmp then save in file.
CString filename;
filename.Format(_T("..\\..\\My
Documents\\barcode\\snapshot%d.bmp"), snapshotno++);
imgBar = new CDIBSectionLite();
imgBar->SetBitmap(bmp);
imgBar->Save(filename);
EndWaitCursor();
•
Load from file then, display on screen, finally, anaysis it
if (imgBar->Load(filename))
{
TRACE(L"\n File opened")
ImageProcessing is very important becasue will done all process:
ImageProcessing(bmp_image,pDC,this,decode,ptrDest ,depth);
2. #include "SDIOCam.h"
(SDIOCam.h, find it in header files in solution’RTBCRwithPDA’)
All of code for a Camera, in APPENDIX A
3. #include "Core.h"
All procedures are carried out according to the settings, this class is hold in list
solution RTBCRwithPDA but can find it in RTBCRwithPDADlg.cpp same name
above or
search on [ImageProcessing(bmp_image,pDC,this,decode,ptrDest
,depth);] then, clik right-on-muse on ImageProcessing, after that, will see list,
chosse Go To Definition go onto code core.
void ImageProcessing(Image &img, CDC *pDC, LPVOID param, DecodeEAN
&decode, byte * imgArray, int bitdepth);
void ScreenPlotter(CDC &MemDC, CDC *pDC, const int &monitor);
void DrawBox(CDC *pDC, DecodeEAN &decode,const int &box);
void DrawLine(CDC *pDC, DecodeEAN &decode,const int &line,const int &i);
72
void ImageProcessing(Image &img, CDC *pDC, LPVOID param, DecodeEAN
&decode, byte * imgArray, int bitdepth)
CPen pen(PS_SOLID, 2, RGB(255, 0, 0)); bounds to image barcode on screen
pDC->SelectObject(pen);
inline void ImageProcessing(Image &img, CDC *pDC, LPVOID param,
DecodeEAN &decode, byte * imgArray, int bitdepth);
inline void ScreenPlotter(CDC &MemDC, CDC *pDC, const int &monitor);
inline void DrawBox(CDC *pDC, DecodeEAN &decode,const int &box);
inline void DrawLine(CDC *pDC, DecodeEAN &decode,const int &line,const int
&i);
inline void ImageProcessing(Image &img, CDC *pDC, LPVOID param,
DecodeEAN &decode, byte * imgArray, int bitdepth)
Bounds to image barcode on screen :
CPen pen(PS_SOLID, 2, RGB(255, 0, 0));
pDC->SelectObject(pen);
4. #include "Image.h"
(Image.cpp, find it in source files in solution’RTBCRwithPDA’) It will do some
progress for image. Adjusts image brightness, Restores FPU register state for
FPU operations, Performs color correction on image pointed by MemDC. R, G
and B are integer values to be added to the existing image. R, G, B values are
applied to all pixels in the image. Alpha channel is ignored, Adjusts image
contrast, creates a new image in the memory buffer (x Width of the image, y,
Height of the image, depth Bit depth of the image.), Performs memory cleanup,
and frees up memory, void FilterGaussianBlur(); void FilterLaplacian(); void
FilterSmooth(); void FilterSobel(); void FilterUnsharpen(),Gets the gray level
value of a pixel pointed by the coordinate x,y or offset, loads internal object
memory buffer with a 32-bit image pointed by MemDC, Converts a color image
to a grayscale image, Inverts a grayscale image, Returns a pointer to the
grayscale image array, Rotates the grayscale image in memory buffer by
specified given degrees, Copies image from object image buffer to target
compatible device context. Available as Device-Independent or DeviceDependent Bitmaps functions.
73
void Image::ColorCorrection(const int &R, const int &G, const int &B);Performs
color correction on image. R, G and B are integer values to be added to the
existing image. R, G, B values are applied to all pixels in the image.
5. #include "Data.h"
(Data.cpp, find it in source files in solution’RTBCRwithPDA’) General const,
size for show an image barcode and General Variable, size for *.bmp ( W & H)
6. #include "DecodeEAN.h"
(DecodeEAN.cpp, find it in source files in solution’RTBCRwithPDA’) Decoding
Class Library Reference for EAN-13, clears the result in memory, scans the
image for barcode and decodes it, obtains image width and height,
#include "DecodeEAN.h"
#include "Image.h"
#include "Barcode.h"
#include <math.h>
#define black 0
#define white 255
// The black color is (0).
// The white color is (255).
DecodeEAN::DecodeEAN()
{
Clear();
The sympols for code to barcode between "".
code="";
Dash "-" between name and number for barcode.
dash="-";
Barcode EAN-13.
ean=" (EAN-13)";
Barcode Guard between start and end.
EnableChkHeight=1;
GuardBarTolerance=(float) 0.4;
tolerance=10;
ModeDecode=1;
ModeGuardbar=1;
ModeNormalize=1;
Mode1stchar=1;
74
ModeGetWidth=1;
height2width_ratio=10;
Continuous all code …..
75
APPENDIX C
Some Types of digital camera card
1.1 HP Photosmart Mobile 1.3MP Camera
The HP Photosmart mobile camera allows consumers to turn their HP iPAQ
Pocket PC into a mobile digital imaging center. By putting the power of digital
imaging in their pocket, users can produce great 4 x 6 snapshots with 1.3-mega pixel
total resolution and 4x digital zoom, or capture video clips with audio to playback on
their iPAQ Pocket PC or desktop computer anywhere, at any time, see figures below.
Specifications:
1. 1.3 MP total resolution
2. 4x digital zoom
3. 1-bit SDIO interface
4.Video capture with audio
76
1.2 Pretec SD Camera 1.3MP SmartCam
The Pretec 1.3Mp CompactCamera is a full-featured digital still and digital video
camera card that can be used on any Pocket PC or Pocket PC 2002 PDA with a
CompactFlash Type I interface slot. The 1.3Mp CompactCamera is capable of taking
photos of up to 1.3 Megapixel resolution. It also features a 2X digital zoom. Several
image quality settings allow you to adjust the JPEG compression level to get the
perfect balance between the file size of the image file and its quality. The 180-degree
swivel head design allows you to view yourself, an automatically adjusted upright
view of the scene you are facing if you rotate the head all the way in the opposite
direction, or all angles in between. Organize your photos and video clips into colorful
albums, even add text and audio annotations for your favorite files. Capture the
moment with the 1.3Mp CompactCamera! Your photos and video are all stored
directly in your Pocket PC's main memory, from which you may upload to your PC
for viewing, editing, and sharing, see figures below.
1.3 Spectec 1.3 Mega Pixel SD Camera for Pocket Pc and Palm
Superb SD camera that works in Pocket PC and Palm OS devices - the drivers are
already installed on the card so it is quick and simple to use.
At A Glance - Spectec SD 1.3 Mega Pixel Camera Camera Design:
•
Digital Zoom: 1x,2x, and 4x
•
Swivel lens allows you to point in multiple directions in a 180° range
77
•
Secure Digital I/O (SDIO) type, suitable for all Pocket PC and Palm PDA
which have SDIO slots hardware
•
The live preview window size is from 160 x 120 to 320 x 240 (full screen).
•
Self-view / portrait / landscape display mode.
•
Full Screen display at 320x240 landscape (240x320 portrait)
•
Supports to capture still images in JPEG, BMP and GIF formats.
•
Image size from 320x240 (240x320) to 480 x 640 (640 x 480) at true colours.
•
Three different imaging controls (auto gain control, auto white balance and
auto-exposure), see figures below.
1.4 Veo Cancels 1.3MP Camera
Veo Cancels 1.3MP Camera, turn your Pocket PC handheld into a 1.3
megapixel camera! Get close with a 4x digital zoom, record and send video clips,
and print high quality 3" X 5" pictures. that already have to create a 1.3 Megapixel
camera. Simply install the drivers, plug the 130S into your SD expansion slot and
within seconds. "With the release of our Photo Traveler 130S for Pocket PC, see
figures below.
78
Figure: Veo Cancels 1.3MP Camera
79
APPENDIX D
SOME BARCODE IMAGE ARE VERY CLEAR
80
APPENDIX E
SCREENSHOTS OF COMMERCIAL TEST PROGRAMS
Interface program visual studio 2005 when created program on a PDA
81
82
APPENDIX F
Number System (number of countries)
The number system consists of two digits (sometimes three digits) which
identify the country (or economic region) numbering authority which assigned the
manufacturer code. Any number system which starts with the digit 0 is an EAN-13
barcode. The valid number system codes are presented in the following table:
Table of number system
00-13: USA & Canada
20-29: In-Store Functions
30-37: France
40-44: Germany
45: Japan (also 49)
46: Russian Federation
471: Taiwan
474: Estonia
475: Latvia
477: Lithuania
479: Sri Lanka
480: Philippines
482: Ukraine
484: Moldova
485: Armenia
486: Georgia
487: Kazakhstan
489: Hong Kong
49: Japan (JAN-13)
50: United Kingdom
520: Greece
528: Lebanon
529: Cyprus
531: Macedonia
535: Malta
539: Ireland
54: Belgium &
Luxembourg
560: Portugal
569: Iceland
57: Denmark
590: Poland
594: Romania
599: Hungary
600 & 601: South Africa
609: Mauritius
611: Morocco
613: Algeria
619: Tunisia
622: Egypt
625: Jordan
626: Iran
64: Finland
690-692: China
70: Norway
729: Israel
73: Sweden
740: Guatemala
741: El Salvador
83
742: Honduras
743: Nicaragua
744: Costa Rica
746: Dominican
750: Mexico
759: Venezuela
76: Switzerland
770: Colombia
773: Uruguay
775: Peru
777: Bolivia
779: Argentina
780: Chile
784: Paraguay
785: Peru
786: Ecuador
789: Brazil
80 - 83: Italy
84: Spain
850: Cuba
858: Slovakia
859: Czech Republic
860: Yugloslavia
869: Turkey
87: Netherlands
880: South Korea
885: Thailand
888: Singapore
890: India
893: Vietnam
899: Indonesia
90 & 91: Austria
93: Australia
94: New Zealand
955: Malaysia
977: International
Republic
Standard Serial Number
for Periodicals (ISSN)
978: International
979: International Standard
Standard Book
Music Number (ISMN)
Numbering (ISBN)
981 & 982: Common
Currency Coupons
99: Coupons
980: Refund receipts