Description: Propose a wavelet transform and co-occurrence matrix for the textile image defect detection method. First, the gray image is decomposed into sub-band and then the texture image into non-overlapping sub-windows were now feature extraction Finally, defect-free samples of M ahalanob is trained classifier to each child window is divided into defective and non- defects. Practical application of the algorithm textile factory defect detection in the environment. Experimental results show that the decision to focus with a strong ability to improve the detection performance of a band, but also improve the computation efficiency.
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有效的纹理缺陷检测方法_子带共现矩阵法.pdf
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