Hong Zhang1,*, Jiaming Zhou1, Qi Wang1, Chengxi Zhu1, Haijian Shao2
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1551-1572, 2023, DOI:10.32604/cmes.2023.027035
Abstract Metal flat surface in-line surface defect detection is notoriously difficult due to obstacles such as high surface
reflectivity, pseudo-defect interference, and random elastic deformation. This study evaluates the approach for
detecting scratches on a metal surface in order to address a problem in the detection process. This paper proposes
an improved Gauss-Laplace (LoG) operator combined with a deep learning technique for metal surface scratch
identification in order to solve the difficulties that it is challenging to reduce noise and that the edges are unclear
when utilizing existing edge detection algorithms. In the process of scratch identification, it is challenging to… More >
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