Marathi Handwritten Numeral Recognition using Zernike Moments and Fourier Descriptors
نویسندگان
چکیده
In this paper, we present a method for automatic recognition of isolated Marathi handwritten numerals in which Zernike moments and Fourier Descriptors are used as features. After preprocessing the numeral image, Zernike moment and the Fourier Descriptor features of the numeral are extracted. These features are then fed in the k-NN classifier for classification. The proposed method is experimented on a database of 12690 samples of Marathi handwritten numeral. We have obtained recognition accuracy of 96. 58% using k-NN classifier.
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