| Abstract |
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Abstract: A recognition system for identifying hand-written Indian (Arabic) numerals for one to nine (9_1) has been developed. A graphical user interface was developed using advanced object oriented techniques that incorporates Matlab as a technical tool. The process involved extracting a feature vector to represent the handwritten sketch based on the "object" centroid and boundary points. A template vector was derived for each digit by taking the average feature vector of 30 different students. The test sketch is compared against all nine templates and a distance measure is performed to make the recognition. An overall hit ratio of 87.22% was achieved in the preliminary results. The ratio reached 100% for some of the digits. But there was misinterpretation between similar digits like (7) and (9). This study is meant to be a seed toward building a recognition system for Arabic language characters.
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 Additional Information
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Index Terms- artificial intelligence, pattern recognition, character recognition, image segmentation, template matching.
Citation:
Faruq Al-Omari,
"Hand-Written Indian Numerals Recognition System Using Template Matching Approaches,"
aiccsa,
p. 0083,
ACS/IEEE International Conference on Computer Systems and Applications (AICCSA'01),
2001
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