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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Handwritten Hindi Character Recognition Using Curvelet Transform
verfasst von : Gyanendra K. Verma, Shitala Prasad, Piyush Kumar
Erschienen in: Information Systems for Indian Languages
Verlag: Springer Berlin Heidelberg
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In this paper, we proposed a new approach for Hindi character recognition using digital curvelet transform. Curvelet transform well approximate the curved singularities of images therefore very useful for feature extraction to character images. A Devanagari script contains more than 49 characters (13 vowels and 33 consonants) and all the characters are rich in curve information. The input image is segmented first then curvelet features are obtained by calculating statistics of thick and thin images by applying curvelet transform. The system is trained with K-Nearest Neighbor classifier. The experiments are evaluated with in-house dataset containing 200 images of character set (each image contains all Hindi characters). The results obtained are very promising with more than 90% recognition accuracy.