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To address the problem of steel strip surface defect detection, a feature fusion-based preprocessing strategy is proposed based on machine vision technology. This strategy can increase the feature dimension of the image, highlight the pixel features of the image, and improve the recognition accuracy of the convolutional neural network. This method is based on commonly used image feature extraction operators (e.g., Sobel, Laplace, Prewitt, Robert, and local binary pattern) to process the defect image data, extract the edges and texture f
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