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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2006, Vol. 7 Issue (9): 1516-1521    DOI: 10.1631/jzus.2006.A1516
Shape Analysis & Matching     
Texture classification based on EMD and FFT
XIONG Chang-zhen, XU Jun-yi, ZOU Jian-cheng, QI Dong-xu
School of Information Science and Technology, Sun Yat-sen University, Guangzhou 510275, China; Information Science School, Guangdong University of Business Studies, Guangzhou 510320, China; College of Science, North China University of Technology, Beijing 100041, China
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Abstract  Empirical mode decomposition (EMD) is an adaptive and approximately orthogonal filtering process that reflects human’s visual mechanism of differentiating textures. In this paper, we present a modified 2D EMD algorithm using the FastRBF and an appropriate number of iterations in the shifting process (SP), then apply it to texture classification. Rotation-invariant texture feature vectors are extracted using auto-registration and circular regions of magnitude spectra of 2D fast Fourier transform (FFT). In the experiments, we employ a Bayesion classifier to classify a set of 15 distinct natural textures selected from the Brodatz album. The experimental results, based on different testing datasets for images with different orientations, show the effectiveness of the proposed classification scheme.

Key words： Texture classification      Empirical mode decomposition (EMD)      Fourier transform      Auto-registration      Rotation-invariant     
Received: 26 April 2006     
CLC:  TP37  
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XIONG Chang-zhen
XU Jun-yi
ZOU Jian-cheng
QI Dong-xu
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XIONG Chang-zhen, XU Jun-yi, ZOU Jian-cheng, QI Dong-xu. Texture classification based on EMD and FFT. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2006, 7(9): 1516-1521.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2006.A1516     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2006/V7/I9/1516

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