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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2006, Vol. 7 Issue (6 ): 6-    DOI: 10.1631/jzus.2006.A0969
    
Mean shift texture surface detection based on WT and COM feature image selection
HAN Yan-fang, SHI Peng-fei
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200030, China
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Abstract  Mean shift is a widely used clustering algorithm in image segmentation. However, the segmenting results are not so good as expected when dealing with the texture surface due to the influence of the textures. Therefore, an approach based on wavelet transform (WT), co-occurrence matrix (COM) and mean shift is proposed in this paper. First, WT and COM are employed to extract the optimal resolution approximation of the original image as feature image. Then, mean shift is successfully used to obtain better detection results. Finally, experiments are done to show this approach is effective.

Key words： Mean shift      Wavelet transform (WT)      Co-occurrence matrix (COM)      Texture defect detection     
Received: 05 August 2005     
CLC:  TN911.73  
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HAN Yan-fang
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Cite this article:

HAN Yan-fang, SHI Peng-fei. Mean shift texture surface detection based on WT and COM feature image selection. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2006, 7(6 ): 6-.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2006.A0969     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2006/V7/I6 /6

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