Abstract
This paper describes the classification of a subset of printed or digitized Gujarati characters. Gujarati belongs to the genre of Devanagri scripts from the Indian subcontinent. Very little work is found in the literature for recognition of Indian language scripts. For this paper a subset of similar appearing Gujarati characters was chosen and subjected to classification by different classifiers. The sample and test images for the characters were obtained from digital images available on the Internet and from scanned images of printed Gujarati text. For their classification, the Euclidean Minimum Distance and the k-Nearest Neighbor classifiers were used with regular and invariant moments. The characters were also classified in the binary feature space using Hamming Distance classifier. The paper presents the recognition rates for these classifiers. A recognition rate of 67% is achieved.
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