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Crack Detection Algorithm based on the Fusion of Percolation Theory and adaptive canny operator

Crack Detection Algorithm based on the Fusion of Percolation...

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第37届中国控制会议

作者： Yana XIAO Junyi Li Guangdong Science & Technology Infrastructure Center Guangdong Computation Technology Application Research Institute

In the process of low voltage current transformer surface crack detection, aimed at the problem of inaccurate edge localization of penetration algorithm and poor crack connectivity detected by adaptive canny algorithm, this paper proposes a new crack detection method based on the fusion of percolation algorithm and adaptive canny operator. The crack gray-scale image is processed by the percolation algorithm to get binary image of crack and this binary image is named Image-A, while the crack gray-scale image is also processed by the adaptive canny operator to get binary image of crack and this binary image is named Image-B. Using wavelet transform to extract low-frequency and high-frequency components of Image-A and Image-B, and the low frequency and high frequency components of the two binary images are respectively superposed. The superposed low frequency and high frequency images are inverse transformed to obtain a fusion image. The fused image is the final cracked image. Experimental results show that the edge information extracted by the proposed algorithm is more abundant than the penetration algorithm, and the continuity of the crack is better than the adaptive canny algorithm and the unilateral detection is reduced. The new crack detection algorithm combines the strong continuity of penetration algorithm with the accurate edge localization ability of adaptive canny algorithm, which is a more effective method of crack detection.

关键词： crack detection fusion method penetration algorithm adaptive canny operator

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