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Volume 21 Issue 3
May  1999
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Xu Chaolun, Wang Xiaoxiang, Ke Youan. TEXTURE CLASSIFICATION BY WAVELET TRANSFORM[J]. Journal of Electronics & Information Technology, 1999, 21(3): 404-407.
Citation: Xu Chaolun, Wang Xiaoxiang, Ke Youan. TEXTURE CLASSIFICATION BY WAVELET TRANSFORM[J]. Journal of Electronics & Information Technology, 1999, 21(3): 404-407.

TEXTURE CLASSIFICATION BY WAVELET TRANSFORM

  • Received Date: 1997-08-25
  • Rev Recd Date: 1998-06-07
  • Publish Date: 1999-05-19
  • This paper describes the characterization of texture properties at multiple scales and orientations using the wavelet transform, and introduces a new wavelet feature suitable for textured image classification. It is pointed out that the new feature is superior to conventional energy measurement by analyzing its stability and its visual proterty in detail. Finally, nine kinds of natural images are classified successfully based on wavelet feature using BP neural network. The results demonstrate natural textured images can be classified without error and done at higher correct classification rate under white noise.
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  • Coggins J M, Jain A K. A spatial filtering approach to texture analysis[J].Pattern Recognition Lett.1985, 3:195-203[2]Chang T, Kuo J. Texture analysis and classfication with tree-structured wavelet transform. IEEE Trans. on Image Processing, 1993, IP-2(4): 429-441.[3]Mallat S. Multifrequency channel decomposition of images and wavelets models. IEEE Tans. on ASSP, 1989, ASSP-37(12): 429-441.[4]余越.子波变换理论及其在信号处理中的应用研究:[博士论文]. 北京:北京理工大学,1996.[5]徐朝伦.基于子波变换和模糊数学的图像分割研究:[博士论文]. 北京: 北京理工大学,1998.[6]张静远,等.基于小波神经网络的声纳信号特征提取与分类.神经网络理论与应用研究96,1996,460-463.
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