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Journal of Zhejiang University SCIENCE A 2009 Vol.10 No.2 P.247~252

http://doi.org/10.1631/jzus.A0820145


A novel texture clustering method based on shift invariant DWT and locality preserving projection


Author(s):  Rui XING, San-yuan ZHANG, Le-qing ZHU

Affiliation(s):  School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   xingrui@zju.edu.cn

Key Words:  Shift invariant DWT, Texture signature, Local preserving clustering, Dimension reduction, k-means


Rui XING, San-yuan ZHANG, Le-qing ZHU. A novel texture clustering method based on shift invariant DWT and locality preserving projection[J]. Journal of Zhejiang University Science A, 2009, 10(2): 247~252.

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%A Le-qing ZHU
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T1 - A novel texture clustering method based on shift invariant DWT and locality preserving projection
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A0820145


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.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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