B.Sc. Hons. in Software Engineering
CW228
Design Manual
Project Title:
Number Plate
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Recognition
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Supervisor:
Nigel Whyte
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Student ID:
C00131013
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Student Name:
Ronghua Ou
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Date:
January 13, 2011
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Table of Contents
1. Introduction ................................................................................................................................ 3
2. Architectural Design .................................................................................................................... 4
3. Interfaces Design......................................................................................................................... 6
3.1
GUI Design ........................................................................................................................ 6
3.2
Menu Design ..................................................................................................................... 7
4. Modular Design ........................................................................................................................... 8
4.1
Modular Design Overview ................................................................................................ 8
4.2
Module of grayscale ......................................................................................................... 9
4.2.1 Detailed description of ........................................................................................... 9
4.3
Module of Edge Detection .............................................................................................. 10
4.3.1 Detailed Description............................................................................................. 11
4.4
Module of Localization ................................................................................................... 11
4.4.1 Detailed description of ......................................................................................... 12
4.5
Module of Segmentation ................................................................................................ 12
4.5.1 Detailed Description............................................................................................. 13
4.6
Module of Character Segmentation ............................................................................... 14
4.6.1 Detailed Description............................................................................................. 14
5. Use case design ......................................................................................................................... 15
5.1
Brief Use Case ................................................................................................................. 15
5.2
System Sequence Diagram ............................................................................................. 17
5.3
Domain model diagram .................................................................................................. 19
6. Conclusions ............................................................................................................................... 20
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1. Introduction
The document presents designs in each part of the NPR system. The NPR system can read the
registration number automatically from the number plate area in digital image and change the
number into plain ASCII text. Because project doesn’t include the hardware part of NPR system,
so this document only describes software design which including Architectural Design,
Interfaces Design, and Modular Design.
Architectural design describes relationship between layers and what each layer actually doing.
Interfaces Design describes what GUI and other interface looks like, what each interface is the use
for, how interfaces involve the specific algorithm they are related and the effect of each interface.
Modular design describes what and how each module actually work, function and method they are
use, input, output and details describes of each module.
Conclusion reviews the main point of this design document.
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2. Architectural Design
NPR system has six layers which including GUI layer, gray scale layer, edge detection layer,
localization layer, Segmentation layer and Recognition layer.
GUI
User Interface
Original
Image
Import
grayscale
Grayscale Image
Edge Detection
Edge
Detection
Image
GUI
Number Plate Localization
Retangle
Image
Character Segmentation
Segmentation
Image
Character Recognition
Figure 1 NPR system architectural
Grayscale layer is a grayscale algorithm use for convert the imported color image from GUI into
grayscale image. This layer accepts an original image and output a grayscale image for the next
layer.
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Edge detection layer is also an algorithm contains Gaussian smoothing algorithm to removes the
noises from grayscale image first, then canny edge detection algorithm deal with the edge detect
and output an edge image for next layer.
In the next layer (Number plate localization), system looks for the number plate area from Edge
detection image by moving a pre-defined slid window around the image. This kind of area
contains the maximum numbers of white pixel then applies the isolated sub-image which
contains the number plate area to the next layer.
Character segmentation layer is used for separate every single character in the number plate
area from the sub-image by using vertical projection algorithm and outputs a set of sub-images
that contains single characters.
Character recognition layer is final identifies the characters from each sub-images and output
them into text format.
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3. Interfaces Design
3.1 GUI Design
Figure 2 user interface of NPR System
As we can see in figure 2, there are two menus in the top, one main display panel in middle, three
small display panels below the main panel and a status message bar in the bottom. The results of
each step will display in each panel when the system running.
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3.2 Menu Design
Figure 3 menu of file
There are three options in file menu (figure 3): open, run and exit. Open is use for user choosing
and open the image they want to import. Run is use for running the system combine each step,
not separate running and Exit is use for gently exit the system, not force click close button in the
top right.
Figure 4 menu of help
Help menu contains the about menu item which including a user manual, version and copy right
about the system.
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4. Modular Design
4.1 Modular Design Overview
NPR System
Grayscale
Number Plate
Localization
Canny Edge
Detection
Character
Segmentation
open image file
Roughly
Isolation
Gaussian
Smoothing
Binarization
Convert Color
Image into
Grayscale
Plate Resizing
Edge Detection
Vertical
Projection
Character
Recognition
Grid Feature
Method
Figure 5 module design overview
Figure 7 shows the level of each module. There are 5 main sub-modules in NPR System; they are
grayscale module, canny edge detection module, number plate localization module, character
segmentation module, and character recognition module. Details of each module are describe
below.
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4.2 Module of grayscale
grayscale
Convert
original Image
into Grayscale
Open image
Figure 6 modular design of grayscale module
The grayscale sub-module has two steps: open image and grayscale. Image is opened for
grayscale process to convert to a grayscale image.
4.2.1
Detailed description of
Module name: open file
Description: load an image file
Input: image file (.jpg or .bmp)
Main success scenario:
1) Click the Menu “File” in the menu bar.
2) Click the “Open” menu item.
3) The “file open” window pop-up, user can choose the directory, select the file, or type the
file name into the “file name” text field. Click OK selected image will be loaded and
displayed in the main panel of user interface.
Extensions: if user chose a file which is not .jpg or .bmp type or typed a wrong file name, an error
window will friendly appear.
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Module name: convert color image into grayscale
Description: convert the inputted image into grayscale format
Input: original image
Output: grayscale image
Main success scenario:
1) Click once in the main panel which is displaying the original image in the middle of main
interface.
2) Original image displayed in the main panel will be replace to grayscale image.
4.3 Module of Edge Detection
Canny Edge
Detection
Gaussian
smoothing
Edge
detection
Figure 7 canny edge detection module
Sub-module of canny edge detection contains two steps: Gaussian smoothing and Edge detection.
Canny edge detection contains the Gaussian smoothing which can remove the noise of edge
detection image. The grayscale image will be converted into edge detected form by canny edge
detection algorithm.
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4.3.1
Detailed Description
Module name: Canny edge detection
Description: it is a algorithm of edge detection to remove all the other pixels except the edges of
objects in the image.
Input: grayscale image
Output: edge detected image
Main success scenario:
1) Click the main panel by twice.
2) Canny edge detection algorithm will be involve on the grayscale image, including finding
the edge strength by calculating the gradient of the image and remove all the other
useless pixels of the image except edges.
3) The grayscale image displayed in the main panel will be replaced to the edge detected
image.
4.4 Module of Localization
Number
Plate
Localization
Number
Plate
Isolation
Resizing
Figure 8 number plate localization module
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4.4.1
Detailed description of
Module name: number plate localization
Description: localize the number plate area from the edge detected image
Input: edge detected Image
Output: sub-image of number plate area
Main success scenario:
1) Click the main panel by three times.
2) Defined a slide search window moves around in the edge detected image to find the area
that has most edge pixels, it will be the area of number plate. The slide window wills high
light in the edge detected image.
3) Click the Localization panel.
4) Perform plate resizing algorithm to find the exact boundaries of number plate.
5) The isolated number plate sub-image will be displayed in the localization panel.
4.5 Module of Segmentation
Character
Segmentation
Vertical
Projection
Binarization
Figure 9 characte segmentation module
Character segmentation has two steps: binarization and vertical projection. Number plate area
that has been separated from the edge detected image will converted into black and white form
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by perform Binarization algorithm in the module, then the vertical projection algorithm is used
for separate single character of the number plate area.
4.5.1
Detailed Description
Module name: character segmentation
Description: Isolated number plate sub-image will be separated to several part and each part can
be supposed to contains one character.
Input: isolated number plate sub-image
Output: a set of sub-image that contains a character.
Main scenario:
1) Click the Segmentation panel.
2) Convert the number plate area sub-image that has been isolated in last step into binary
image.
3) Involve vertical projection algorithm onto the binary sub-image to separate the single
character.
4) The isolated single character sub-image will be displayed in the segmentation panel.
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4.6 Module of Character Segmentation
Character
Recognition
Grid Feature
Method
Figure 30 character recognition module
Character recognition using an algorithm called grid feature method to identify the each subimage characters of number plate area and output them by text format.
4.6.1
Detailed Description
Module name: character recognition
Description: identify each character in number plate sub-image
Input: a set of segmented sub-image
Output: plate number in text form
Main scenario:
1) Click the Recognition panel.
2) Apply grid feature method onto each segmented sub-image
3) The registration number on the number plate will be displayed in the recognition panel.
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5. Use case design
Figure 11 Use case diagram
5.1 Brief Use Case
Use case: open image
Actor: user
Description: User chooses an image from hard disk. Then system open the image and display in
main panel.
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Use case: Image grayscale
Actor: user
Description: After import image, grayscale converts the original image into gray image. Gray
image then replace the original image in main panel.
Use case: Number plate localization
Actor: user
Description: A slide search window moves around in the edge detected image to find the area
that has most edge pixels, it will be the area of number plate. The slide window wills high light in
the edge detected image. The isolated number plate sub-image will be displayed in the
localization panel.
Use case: Number plate segmentation
Actor: user
Description: Number plate area that has been separated from the edge detected image will
converted into black and white form, then separate single character of the number plate area.
Use case: Number plate recognition
Actor: user
Description: identify the each sub-image characters of number plate area and output them by
text format.
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5.2 System Sequence Diagram
Figure 12 Image grayscale use case of system sequence diagram
Figure 13 Edge detection use case of system sequence diagram
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Figure 14 Number plate localization use case of system sequence diagram
Figure 15 Number plate segmentation use case of system sequence diagram
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Figure 16 Number plate recognition use case of system sequence diagram
5.3 Domain model diagram
Figure 17 Domain model diagram
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6. Conclusions
There are six layers in NPR system; they are GUI layer, gray scale layer, edge detection layer,
localization layer, Segmentation layer and Recognition layer.
User interface has two menus in the top, one main display panel in middle, three small display
panels below the main panel and a status message bar in the bottom. The results of each step
will display in each panel when the system running.
NPR System contain five main modules, they are grayscale module, canny edge detection module,
number plate localization module, character segmentation module, and character recognition
module. Each module gets an input image or a set of sub-image from last module and outputs
processed image to the next module.
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