Electrical & Electronic Engineering |
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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.
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Received: 02 March 2008
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