Performance Comparison of Devanagari Handwritten Numerals Recognition | Zendy

Mahesh Jangid Kartar Singh | Zendy; Renu Dhir | Zendy; Rajneesh Rani | Zendy

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Performance Comparison of Devanagari Handwritten Numerals Recognition

Author(s) -

Mahesh Jangid Kartar Singh,

Renu Dhir,

Rajneesh Rani

Publication year - 2011

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/2551-3496

Subject(s) - devanagari , computer science , numeral system , artificial intelligence , speech recognition , natural language processing , pattern recognition (psychology) , character recognition , image (mathematics)

In this paper an automatic recognition system for isolated Handwritten Devanagari Numerals is proposed and compared the recognition rate with different classifier. We presented a feature extraction technique based on recursive subdivision of the character image so that the resulting sub images at each iteration have balanced numbers of foreground pixels as possible. Database, provided by Indian Statistical Institute, Kolkata, have 22547 grey scale images written by 1049 persons and obtained 98.98% highest accuracy with SVM classifier. Results are compared with KNN and Quadratic classifier.

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