Learn about OCR:
Optical Character Recognition
Track, Trace & Control Solutions
© 2011 Microscan Systems, Inc.
Learn about OCR
About Your Presenter
Presenting today:
Juan Worle
Technical Training Coordinator
Microscan Corporate Headquarters
Renton, WA
© 2011 Microscan Systems, Inc.
Learn about OCR
Course Objectives
By completing this webinar you will:

Understand definition of OCR
A little about the history, and where it is applied today

Know different types of OCR and how OCV is different
Understand how to select the best tools

Know the critical features of OCR fonts
Learn how to identify potential weak points in an application

Know how to identify reliable OCR applications
Become familiar with applications that have been successful and low maintenance
© 2011 Microscan Systems, Inc.
Learn about OCR
Topics




About OCR
OCR and OCV
Decoding OCR
Example applications
© 2011 Microscan Systems, Inc.
Learn about OCR
About OCR
What does OCR mean, and some perspective
 What is OCR?
 A little history
 OCR and Machine Vision
© 2011 Microscan Systems, Inc.
Learn about OCR
What is OCR?
Optical Character Recognition
The conversion of written or typed text into a string of characters formatted
for machines.
© 2011 Microscan Systems, Inc.
Learn about OCR
What is OCR?
Optical Character Recognition

OCR fonts are unique: Unlike barcodes and 2D symbologies, they are both
machine readable and human readable.
– The data is considered less secure than barcodes and 2D symbols.

Some OCR software tools convert paper documents to
electronic documents.
OCR conversion on a PC allows
you to copy scanned text
© 2011 Microscan Systems, Inc.
Learn about OCR
A Little History
OCR has been used commercially since the 1970s.
 Automated bill processing: OCR systems in automated payment
processing facilities
 Retail check-out before UPC: Handheld OCR readers read the
price of merchandise
The first patents were developed in
the 1930s by Gustav Tauschek and
then Paul Handel
© 2011 Microscan Systems, Inc.
Automatic check processing machines
use OCR algorithms and MICR fonts
Learn about OCR
A Little History
Today OCR is used in many specialized applications.
 Search engines
 Handwriting recognition
 Postal tracking and document handling
Google’s powerful OCR software
allows you to search the web
from a mobile phone
Mailing systems use specialized OCR
algorithms for handwriting recognition
© 2011 Microscan Systems, Inc.
Learn about OCR
A Little History
OCR within Machine Vision focuses on industrial applications.
 Automotive, aerospace, semiconductor manufacturing
 Food and beverage handling
 Packaging
Industrial applications for OCR have the following traits:
Fixtured parts
Consistent lighting and environment
Consistent fonts
Example of LOT and DATE codes:
By reading the text, the date can be
checked, and the lot number verified
© 2011 Microscan Systems, Inc.
Learn about OCR
OCR and Machine Vision
There are three uses for OCR and OCV tools.
Presence: Ensure the characters have been marked
–
–
–
Ensure the characters are present
Check the readability of OCR characters
Optical Character Verification (OCV) is common
Tracking: From stock through manufacturing to packaging
–
–
OCR is used to
identify the contents
of unlabeled cans
© 2011 Microscan Systems, Inc.
Lot, batch, expiration dates, serial numbers
A common barcode application
Identification: Identify part or contents of a container
–
–
Ensure proper labeling
Ensure product matches container
Learn about OCR
OCR and OCV
Understand the difference between Recognition and
Verification
 Comparison of OCR and OCV
 Methods to read OCR
© 2011 Microscan Systems, Inc.
Learn about OCR
Comparison of OCR and OCV
OCV: Optical Character Verification
Use OCV tools to check the legibility and quality of text, based on a fixed and
known sequence of characters.

The output of an OCV tool is
a quality report of correctness.
OCR: Optical Character Recognition
OCV: verify quality
The OCR tool is used to read an unknown sequence of characters.

The output of an OCR tool is
machine usable text.
OCR: read text
© 2011 Microscan Systems, Inc.
Learn about OCR
Comparison of OCR and OCV
Verification:
Inspecting characters for content, correctness, quality, contrast and sharpness
compared to stored templates.
Examples:


Date / Lot verification
Component ID verification
–

ABC-123
Label, carton, insert, outsert
Verification of on-line printing
–
–
–
Clinical labels
Blister packs
Direct printing on product
Use OCV to check levels of print
quality and legibility
© 2011 Microscan Systems, Inc.
Learn about OCR
Comparison of OCR and OCV
Reading:
A tool for reading text strings of random content and converting to machine
usable text.




Examples:
Sorting and identification
Serialization
Codes with Time/Date stamp
Verification of readability
– decoded=readable

OCR can be used to read serial
numbers on a data plate
Verification of on-line printing
– Codes with inconsistent character placement or size
– Can verify text using match
© 2011 Microscan Systems, Inc.
Learn about OCR
Methods to Read OCR
Fixed Font:
The font characters must conform to a fixed pattern.
Examples:
– OCR-A, OCR-B: Many printed applications such as passports, documents, and
pharmaceutical labels
– SEMI: Used for semiconductor manufacturing
– MICR: Banking documents such as checks.
© 2011 Microscan Systems, Inc.
Learn about OCR
Methods to Read OCR
Trainable Font:
Any font can be presented and learned by Machine Vision software during
setup, then identified during run-time.
– More common than fixed font because any font or variations can be trained.
– Reviews each character and looks for a match in the trained font library.
Trainable OCR tools let you
use a non-standard font
When using trainable font tools, a character
is not recognized until it is trained
© 2011 Microscan Systems, Inc.
Learn about OCR
Decoding OCR
Understanding the unique traits of an OCR font




Character dimensions
Font characteristics
Print variations
Improve performance
© 2011 Microscan Systems, Inc.
Learn about OCR
Character Dimensions
The overall size of the character matters, as well as the features.
Area
Features
Height
Line
Weight
Width
© 2011 Microscan Systems, Inc.
Learn about OCR
Font Characteristics
The font matters.


Maximize the difference in similar characters for more reliability.
Many characters have very little difference.
Let’s look at the Arial font. The Character O has many similar characters:
O O
CO
QO
G
Original
Arial: High probability of confusion
© 2011 Microscan Systems, Inc.
Letter C
80% match
Letter Q
75% match
Letter G
70% match
Learn about OCR
Font Characteristics
Fonts designed for machine reading work best.



Uniform character spacing
Each character designed to be different than all others
DPM applications
There are also several fonts designed for Inkjet and
Direct Part Mark (DPM) applications
Even character separation improves readability
Good:
Verdana Sample
But better:
Low probability of confusion: OCR-A
is designed for machine reading and has
differences in similar characters
© 2011 Microscan Systems, Inc.
OCR Sample
Learn about OCR
Print Variations
Even if the text looks good on screen, printers can change
appearance.
Print considerations
SKEW
DPM considerations
Dot Size
N L
DEFECTS
Overprint Underprint
SCALE
Dot Spacing
Skew
Dot offset
LINE WEIGHT
Tip: Avoid large gaps when marking characters.
© 2011 Microscan Systems, Inc.
Learn about OCR
Print Variations
The substrate (the material you are printing on) can affect readability.



Ink absorption
Background noise
Damaged characters
Background noise can
cause character confusion
Damaged characters and uneven
surfaces can affect decodability
© 2011 Microscan Systems, Inc.
Learn about OCR
Improve Performance
There are many ways to improve performance.



Use trainable font tools for more tolerance
– Teach variations of a font – Slight rotations
– Line weight
– Focus
Leave a quiet zone that is 2-3x character space
Use additional Machine Vision tools
– Morphology: modify the image
– Dynamic location: use an anchor point
Original
Line weight
De-focus
Line weight
Teach variations of the font
for more reliable reading
© 2011 Microscan Systems, Inc.
Dynamic location is helpful if
the part location moves
Morphology: Vision tools that can
improve the appearance of an image
Learn about OCR
Improve Performance
Recommendations when using Microscan products.




Use at least a 6 point font size
Adjust camera to font for 25 pixels wide/30 pixels high
Space between each character should be at least 1 point (0.015”)
– Half the size of the character works best
The smallest features within a character (like Line weight) should be at least
1 point (0.015”)
Feature
size > .015”
AB
Ideal space between characters is
half the character size
© 2011 Microscan Systems, Inc.
30 Pixels
25 Pixels
Learn about OCR
OCR Applications
Some common OCR applications




Print verification
Label verification
Date and Lot code tracking
Part identification
© 2011 Microscan Systems, Inc.
Learn about OCR
Print Verification
Continuous ink-jet (CIJ) on cartons.
 Validate the data
 Combine with barcode tool
 Feedback when the head should be cleaned
© 2011 Microscan Systems, Inc.
Learn about OCR
Label Verification
Ensure the proper label is applied.
 Several products are run on a single line
 Report error when incorrect label is applied
© 2011 Microscan Systems, Inc.
Learn about OCR
Date and Lot Code Tracking
Date and Lot code traceability.
 Validate and verify printing
 Track products through manufacturing
 Conform to regulations (FDA)
© 2011 Microscan Systems, Inc.
Learn about OCR
Part Identification
Identify gasket for installation.
Read the part number to ensure the correct part is installed
© 2011 Microscan Systems, Inc.
Learn about OCR
Learn about OCR
Conclusion
 The idea of OCR is not new; it has been around since the 1930s. Industrial
applications gained momentum in the 1970s.
 Today OCR tools are used in many non-industrial applications. Machine Vision
OCR tools focus on industrial applications.
 OCR tools can be categorized by OCV, OCR Fixed Font or OCR Trainable Font.
 The features of a font are important and can determine the success of an
application.
– Font selection
– Substrate and marking method
– Probability of confusion
– Character separation
– Printer variables
– Character dimensions
 The most common Machine Vision applications include Presence, Tracking, and
Identification.
© 2011 Microscan Systems, Inc.
© 2011 Microscan Systems, Inc.
Learn about OCR
Thank you!
For more information
Website: www.microscan.com
–
–
–
–
Online courses
Spec sheets
Technology brochures
Support self-help and support request form
Graduation exercise
Download Visionscape from
www.microscan.com download center
Instructor:
Juan Worle, Technical Training Coordinator
Email: jworle@microscan.com
Feedback on this webinar: www.microscan.com/feedback
Additional contacts:
Product information: info@microscan.com
Training: training@microscan.com
Support: helpdesk@microscan.com
© 2011 Microscan Systems, Inc.