Abstract
This paper puts forwards a method of using MGabor filter-banks to extract Texture-Color features from digital images, and then to construct a group of support vector machines (SVM) classifiers to automatically and accurately classify color digital images. Successful experiments are conducted on the Simplicity and Brodatz image set and our own Ancient shards image sets. The experiments results show the proposed method can integrate the texture features and color information to further improve distinguishing ability of each category images.
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© 2012 Springer-Verlag Berlin Heidelberg
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Wang, K., Qi, L., Geng, G. (2012). Images Classifications Based on Color-Texture Feature. In: Lei, J., Wang, F.L., Deng, H., Miao, D. (eds) Artificial Intelligence and Computational Intelligence. AICI 2012. Lecture Notes in Computer Science(), vol 7530. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33478-8_14
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DOI: https://doi.org/10.1007/978-3-642-33478-8_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33477-1
Online ISBN: 978-3-642-33478-8
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