RECOGNITION OF ISOLATED HANDWRITTEN KANNADA VOWELS

Sangame S.K.¹*, Ramteke R.J.², Rajkumar Benne³*
¹Department of Computer Science, North Maharashtra University, Jalagaon
²Department of Computer Science, North Maharashtra University, Jalagaon
³P.G Department of Studies and Research in Computer Science, Gulbarga University, Gulbarga
* Corresponding Author : rgbenne@yahoo.com

Received : -     Accepted : -     Published : 21-12-2009
Volume : 1     Issue : 2       Pages : 52 - 55
Adv Comput Res 1.2 (2009):52-55

Keywords : OCR, Indian Language, Kannada Vowels, Moment inva riants
Conflict of Interest : None declared

This paper presents unconstrained handwritten Kannada vowels recognition based upon invariant moments. The proposed system extracts Invariant moments feature from zoned images. A Euclidian distance criterion and K-NN classifier is used to classify the handwritten Kannada vowels. A total 1625 image are considered for experimentation and overall accuracy found to be 85.53%. The novelty of the proposed method is independent of size, slant, orientation, and translation in handwritten characters.

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