1. Optical Data Capture: Optical Character Recognition (OCR)
Intelligent Character Recognition (ICR)
Intelligent Recognition
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

2. Bangkok, Thailand, 15-19 September 2008
Summary
Concept/Definition
Forms Design
Scanners & Software
Storage
Accuracy
OCR/ICR Advantages and Disadvantages
Intelligent Recognition (IR)
Commercial Suppliers
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

3. Definition/Concept of OCR
Gives scanning and imaging systems the ability to turn images of machine printed characters into machine readable characters.
Images of the machine printed characters are extracted from a bitmap of the scanned image
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

4. Definition/Concept of ICR
Gives scanning and imaging systems the ability to turn images of hand written characters into machine readable characters
Images of the hand written characters are extracted from a bitmap of the scanned image
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

5. OCR and ICR Differences
OCR is less accurate than OMR but more accurate than ICR
ICR will require editing to achieve high data coverage
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

6. Bangkok, Thailand, 15-19 September 2008
Forms
OCR/ICR has less strict form design compared to OMR
No timing tracks
Has Registration Marks
ICR requires hand printed boxes filled one alphanumeric character per box
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

7. Bangkok, Thailand, 15-19 September 2008
OCR
Forms
OCR/ ICR is more flexible since:
no timing tracks are required
The image can float on a page
The use of drop color reduces the size of the scanner’s output and enhances the accuracy
ICR/OCR technology often uses registration mark on the four-corners of a document, in the recognition of an image
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

8. Bangkok, Thailand, 15-19 September 2008
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

9. OCR/ICR Scanners and Software
Forms can be scanned through a scanner and then the recognition engine of the OCR/ICR system interpret the images and turn images of handwritten or printed characters into ASCII data (machine-readable characters).
Users can scan up without doing the OCR
Speeds Range from: sheets/min (dependent on the recognition engine)
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

10. OCR/ICR Storage Characteristics
Storage/Retrieval
Images are scanned and stored and maintained electronically
There is no need to store the paper forms as long as you safeguard the electronic files
With OCR/ICR technologies, images can be scanned, indexed, and written to optical media
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

11. Ideal OCR/ICR Accuracy Thresholds
Accuracy achieved by data entry clerks (~99.5%) are approximately equal to OCR/ICR in in perfect tuning (~99.5%)
Up to 99.9% accuracy with editing (like OMR)
The recognition engine must be tuned, tested and validated very carefully
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

12. Bangkok, Thailand, 15-19 September 2008
OCR/ICR Advantages
Advantages
Recognition engines used with imaging can capture highly specialized data sets
OCR/ICR recognize machine-printed or hand-printed characters.
Scanning and recognition allowed efficient management and planning for the rest of the processing workload
Quick retrieval for editing and reprocessing
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

13. OCR/ICR Disadvantages
Technology is costly
May require significant manual intervention
Additional workload to data collectors -ICR has severe limitations when it comes to human handwriting
Characters must be hand-printed/machine-printed with separate characters in boxes
ineffective when dealing with cursive characters
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

14. Bangkok, Thailand, 15-19 September 2008
OMR-OCR/ICR Compared
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

15. OCR/ICR Challenges/Issues
Has corresponding issues with OMR
Algorithm development (Preparation of memory dictionary)
Processing time considerations due to recognition engine
Development costs
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

16. Definition/Concept of IR
State of the art recognition technology
Gives scanning and imaging systems the ability to turn images of hand written and cursive characters into machine readable characters
Images of the hand written and cursive characters are extracted from a bitmap of the scanned image
The ability to capture cursive make this method unique
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

17. Definition/Concept of IR
eight elements that make up the trajectories of all cursive letters (figure 1)
Photo: Parascript LLC
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

18. Definition/Concept of IR
Intelligent Recognition dynamically uses context
context is used during the recognition process, improving the accuracy of results
Contexts helps to identify letters where the symbol segmentation of an image is ambiguous
Photo: Parascript LLC
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

19. Bangkok, Thailand, 15-19 September 2008
Technology Evolution
FORM TYPES
TEXT STYLES
No special form design
No constraining boxes or combs
Condensed strings
Cursive
Dirty & Noisy forms
Bad quality paper
Legacy Forms
Bad quality
machine print
Unconstrained
Handprint
Specially designed for automatic
recognition
Constrained
Handprint
Constraining boxes or combs
Drop out ink for preprinted
text & boxes
Machine Print
Intelligent
Recognition
OCR
ICR
TECHNOLOGY EVOLUTION
Illustration: Conference on Technology Options for 2011 Census
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

20. Major Commercial Suppliers
Top Image Systems (TIS) (
ReadSoft (
Teleform (
Scanner Suppliers
Fujitsu, Canon, Bell & Howell, Kodak
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008

21. Bangkok, Thailand, 15-19 September 2008
THANK YOU!
UNSD-UNESCAP Regional Workshop on Census Data Processing: Contemporary technologies for data capture, methodology and practice of data editing, documentation and archiving
Bangkok, Thailand, September 2008