Abstract:  Aiming at the difficulty of detecting subtle defects on O-ring surface, we present a method of detecting defects on O-ring surface based on six photometric stereoscopic method and image comprehensive feature analysis. First, the images of six different light source angles are collected, and the surface gradient map and reflectance map are reconstructed by photometric stereoscopic method. The surface gradient image is first converted into the average curvature and Gaussian curvature image, and then converted into the gray-scale image. The defect region is segmented using a fixed threshold. After the reflectivity map is filtered by Gauss, the local mean and variance thresholds are used to segment the defect area. Finally, the defects are accurately selected by analyzing the connected domain characteristics of the obtained defect regions. The experimental test results show that it has a good effect on the subtle defects such as weld marks, concave-convex and flow marks on the surface of the seal ring. In the application of the designed seal ring quality detection system, the detection accuracy is more than 98. 4% , which can solve the problem of low recognition rate of the current industrial sealing ring defect detection.

Key words: machine vision, sealing ring, photometric stereoscopic method, characteristics analysis, appearance defect detection