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Small bearings, axles, and etc are important components for machines,vehicles, engines and etc. In order to improve the detection efficiency and detection accuracy of its surface defects, Taking small bearing surface as the object of study, and putting forward the method to realize real-time online automatic detection of bearing surface defects based on machine vision technology and designing the online automatic detection system of defective parts machine vision based on BP neural network. According to the micro bearings surface structure, size, accuracy and defect characteristics, using machine vision technology, preprocessing for the collected image, and constructing BP neural network detective model, extracting target area in the image by Hough transform and Roberts operator. Based on the combined-moment invariants, the defects of the bearings are judged, and thus the defects of the small bearings are detected in real time.The simulation results of MATLAB verify the reliability and effectiveness of ANN detection model.