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