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Detection of Defect Edge of Aluminum Foils Based on Fuzzy Enhancement and Wavelet Transform

机译:基于模糊增强和小波变换的铝箔缺陷边缘检测

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In order to accurately detect the defects on the aluminum surface, including pinholes, yellow discoloration, oil stains, and scratches, an algorithm combining local fuzzy enhancement, wavelet transform modulus maxima (WTMM) and multi-scale product was proposed. First, the defect areas with low contrast, such as yellow discoloration and oil stains, were located in the HSI color space; then, the local fuzzy enhancement was performed on these edges, thereby highlighting the edge features and reducing the amount of computation; at last, the multi-scale product was calculated, and the binary image of defect edge on aluminum foil was obtained via WTMM. Plenty of experimental results showed that the proposed algorithm could extract clearer and more complete edges and effectively detect the defect edges with low contrast in the aluminum foil image, laying the foundation for the subsequent defect identification.
机译:为了准确地检测铝表面上的缺陷,包括针孔,黄色变色,油渍和划痕,提出了一种组合局部模糊增强,小波变换模量最大值(WTMM)和多尺度产品的算法。首先,具有低对比度的缺陷区域,如黄色变色和油渍,位于HSI颜色空间中;然后,对这些边缘进行局部模糊增强,从而突出显示边缘特征并降低计算量;最后,计算多尺度产品,通过WTMM获得铝箔上的缺陷边缘的二值图像。大量的实验结果表明,该算法可以提取更清晰和更完整的边缘,并有效地检测铝箔图像中具有低对比度的缺陷边缘,为后续缺陷识别奠定了基础。

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