Application of ROI-based image processing technology in mechanical component size measurement

In the context of high automation and precision manufacturing, dimensional measurement and defect detection of mechanical parts become the key to ensuring product quality. An image processing technique based on region of interest (ROI) is proposed to detect all surface defects of bearing rings. By designing and optimizing the whole surface defect detection system framework of the bearing ring, combining binarization and morphology processing technology, the method realizes efficient and accurate defect detection. Specific methods include image preprocessing, ROI extraction and defect feature analysis for the whole surface of bearing rings. The experimental results show that the method has excellent performance in the detection accuracy, the error rate of good products and the missing rate of defective products. The detection accuracy is as high as 0.97, the error rate of good products is as low as 0.08%, and the missing rate of defective products is as low as 0.98%. These results show that the method proposed in this study has significant advantages in improving the efficiency and accuracy of mechanical parts inspection, and provides an effective solution for precision manufacturing and intelligent quality control.