Texture image classification using complex texton

Authors:
Zhenhua Guo;Qin Li;Lin Zhang;Jane You;Wenhuang Liu;Jinghua Wang
Affiliations:
Graduate School at Shenzhen, Tsinghua University, Shenzhen, China;Department of Computing, The Hong Kong Polytechnic University, Hong Kong;Department of Computing, The Hong Kong Polytechnic University, Hong Kong;Department of Computing, The Hong Kong Polytechnic University, Hong Kong;Graduate School at Shenzhen, Tsinghua University, Shenzhen, China;Department of Computing, The Hong Kong Polytechnic University, Hong Kong
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Year:
2011

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Abstract

Statistical textons has shown its potential ability in texture image classification. The maximal response 8 (MR8) method extracts an 8-dimensional feature set from 38 filters. It is one of state-of-the-art rotation invariant texture classification methods. This method assumes that each local patch has a dominant orientation, thus it keeps the maximal response from six responses of different orientations in the same scale. To validate whether local dominant orientation is necessary for texture classification, in this paper, a complex texton, complex response 8 (CR8), is proposed. The average and standard deviation of filter responses for different orientations is computed, and then an 8-dimensional complex texton is extracted. After using k-means clustering algorithm to learn a texton dictionary, a histogram of texton distribution could be built for a given image. Experimental results on one large public database show that CR8 could get comparable results with MR8.