An image-processing pipeline built from Gaussian filtering, Canny edges, SAD/SSD matching, and HSV thresholding is reported to classify motor control boards at over 99% accuracy, but without released data or baselines the claim is not yet independently supported.
Deep Convolution Neural Network for Image Recognition
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Research on Defect Detection Method of Motor Control Board Based on Image Processing
An image-processing pipeline built from Gaussian filtering, Canny edges, SAD/SSD matching, and HSV thresholding is reported to classify motor control boards at over 99% accuracy, but without released data or baselines the claim is not yet independently supported.