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Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2009, Vol. 10 Issue (2): 247-252    DOI: 10.1631/jzus.A0820145
Electrical & Electronic Engineering     
A novel texture clustering method based on shift invariant DWT and locality preserving projection
Rui XING, San-yuan ZHANG, Le-qing ZHU
School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
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Abstract  We propose a novel texture clustering method. A classical type of (approximate) shift invariant discrete wavelet transform (DWT), dual tree DWT, is used to decompose texture images. Multiple signatures are generated from the obtained high-frequency bands. A locality preserving approach is applied subsequently to project data from high-dimensional space to low-dimensional space. Shift invariant DWT can represent image texture information efficiently in combination with a histogram signature, and the local geometrical structure of the dataset is preserved well during clustering. Experimental results show that the proposed method remarkably outperforms traditional ones.

Key wordsShift invariant DWT      Texture signature      Local preserving clustering      Dimension reduction      k-means     
Received: 02 March 2008     
CLC:  TP391  
Cite this article:

Rui XING, San-yuan ZHANG, Le-qing ZHU. A novel texture clustering method based on shift invariant DWT and locality preserving projection. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2009, 10(2): 247-252.

URL:

http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.A0820145     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2009/V10/I2/247

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