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Handwritten Malayalam Character Recognition using Curvelet Transform and ANN

Manju Manuel, R SaidasS.

Malayalam, the official language of Kerala, a southern state of India has been accorded the honour of language of eminence. Hence the researches in recognition and related works in Malayalam language is gaining more prominence in the current scenario. This paper proposes the use of Curvelet transform and neural network for the recognition of handwritten Malayalam character. Curvelet transform is to be used in the feature extraction stage and neural network for classification. Curvelet transform provides a compact representation for curved singularities and is well suited for malayalam language. Two different back propagation algorithms had been employed and the performance is compared on varying architecture. The promising feature of the work is successful classification of 53 characters which is an improvement over the existing works. Application of character recognition include sorting of bank cheques and postal letters, reading aid for blind, data compression etc. Besides, an automated tool with graphical user interface in MATLAB has been developed for Malayalam character recognition. General Terms Pattern Recognition, Artificial Neural Network (ANN), Curvelet Transform, Optical character recognition (OCR),

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