DocumentCode :
2600088
Title :
Improvement of OCR Accuracy by Similar Character Pair Discrimination: an Approach based on Artificial Immune System
Author :
Garain, Utpal ; Chakraborty, M.P. ; Majumder, D. Dutta
Author_Institution :
Indian Stat. Inst., Kolkata
Volume :
2
fYear :
0
fDate :
0-0 0
Firstpage :
1046
Lastpage :
1049
Abstract :
Artificial immune system (AIS) based classification approach is relatively new in the field of pattern recognition (PR). This paper explores this paradigm in the context of a frequently occurring PR problem, namely discrimination of similar shaped character pairs. The problem has been studied in the context of improving the recognition accuracy of OCR (optical character recognition) systems that often make mistakes to properly classify the confusion pairs. A set of binary classifiers is designed following immune principles to achieve pair-wise discrimination. The performance of the proposed approach has been investigated in detail and compared with classification schemes like nearest neighbor and support vector machines (SVM) based approach
Keywords :
artificial life; optical character recognition; pattern classification; support vector machines; artificial immune system; character pair discrimination; optical character recognition systems; pattern recognition; support vector machines; Artificial immune systems; Character recognition; Electronic mail; Immune system; Intrusion detection; Nearest neighbor searches; Optical character recognition software; Pattern recognition; Support vector machine classification; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
ISSN :
1051-4651
Print_ISBN :
0-7695-2521-0
Type :
conf
DOI :
10.1109/ICPR.2006.697
Filename :
1699387
Link To Document :
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