Abstract
This paper proposes an efficient method based on texture feature for text-independent writer identification. In order to extract texture feature, we use the modified 2-D Gabor filter, which can decompose the image into sub-bands with different frequencies and orientations. Nearest neighbor classifier based on weighted chi-square distance is utilized in classification. The experiments on a database containing 203 writers of address images demonstrate that the performance of our modified 2-D Gabor filter is better than that of the traditional 2-D Gabor filter and our proposed method achieves promising results.
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Wang, D., Wen, Y., Lu, Y. (2012). Text-Independent Writer Identification Using Texture Feature. In: Zhang, W., Yang, X., Xu, Z., An, P., Liu, Q., Lu, Y. (eds) Advances on Digital Television and Wireless Multimedia Communications. Communications in Computer and Information Science, vol 331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34595-1_23
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DOI: https://doi.org/10.1007/978-3-642-34595-1_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34594-4
Online ISBN: 978-3-642-34595-1
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