A WAVELET TRANSFORMATION BASED MULTICHANNEL NEURAL NETWORK METHOD FOR TEXTURE SEGMENTATION
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TP391.41 TN919.8

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    Abstract:

    A neural network texture segmentation method, in which multichannel filtering is embodied, was proposed. Multichannel filtering technology is a very effective method for texture segmentation. Instead of using a general filter bank, the texture feature extraction and classification tasks were performed in this paper by the same unified neural network. Decision based neural network was adopted to improve the accuracy of classification. Wavelet transformation of texture was used to decrease the correlation of texture data and increase the efficiency of networks learning. Experiments show that the proposed method achieves lower error rates than other methods and a satisfactory result is obtained.

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ZHANG Jun QI Fei Hu. A WAVELET TRANSFORMATION BASED MULTICHANNEL NEURAL NETWORK METHOD FOR TEXTURE SEGMENTATION[J]. Journal of Infrared and Millimeter Waves,1998,17(1):54~60

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  • Received:
  • Revised:June 17,1997
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