Optical character recognition systems have been effectively developed for recognizing the printed characters of many non-Indian languages such as English and Chinese. At early stages, few research works were carried out for recognizing the handwritten characters, and now, various efforts are on the way for the development of efficient systems for recognizing the Indian languages, especially for Tamil, a south Indian language widely used in Tamilnadu, Pudhucherry, Singapore, and Srilanka. In this paper, an OCR system is developed for the recognition of basic characters in handwritten Tamil language, which can handle different font sizes and font types. Zernike moments and Legendre polynomial which have been used in pattern recognition are used in this system to extract the features of handwritten Tamil characters. A comparative study is performed in this paper. Feed forward back propagation neural classifier has been used for the classification of Tamil characters.
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