Abstract
In this paper a method for recognition of handwritten characters based on Gabor filters and Zernike moments is discussed. The technique can be summarized as follows: in the preprocessing stage the input image is first normalized. Next the feature extraction is performed. Thus, the image is represented by the feature vector. Mean and standard deviation of the magnitude of the Gabor transform coefficients and the Zernike moments are used as features. Classification is then carried out on the basis of the extracted features.
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© 2007 Springer-Verlag Berlin Heidelberg
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Choras, R.S. (2007). Feature Extraction of Gray-Scale Handwritten Characters Using Gabor Filters and Zernike Moments. In: Kurzynski, M., Puchala, E., Wozniak, M., Zolnierek, A. (eds) Computer Recognition Systems 2. Advances in Soft Computing, vol 45. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75175-5_43
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DOI: https://doi.org/10.1007/978-3-540-75175-5_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75174-8
Online ISBN: 978-3-540-75175-5
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