Circle detection method based on contour extraction and rule verification

Abstract

Product appearance visual inspection is a research hot spot in the field of industrial machine vision technology. In the manufacturing process of Flexible Integrated Circuit Substrate (FICS), the defects of circle hole on FICS surface affect the electrical connection performance between chip and substrate, so detecting the defects of circle hole on FICS surface is an important content of visual inspection. However, the surface of FICS presents local high texture characteristics and the circle hole may have edge defects, which make it difficult to accurately detect the circle hole. To solve this problem, this paper proposes a circle detection method based on contour extraction and rule verification. Firstly, a contour extraction operator is used to extract candidate circular contours from FICS surface images. Secondly, the closed contours are divided into two categories according to the roundness of the contours, where the circle hole verification method based on the Helmholtz principle is used to verify large roundness contours, the iterative least squares method is used to verify small roundness contours. Finally, parameters of the resulted circular holes are calculated to determine whether they are defective circular holes or not. Compared with classical circle detection algorithms such as random circle detection and ED circle detection, the proposed method performs better results in terms of accuracy, precision and speed. The average accuracy and recall of the proposed method are 100%, and the average detection speed is 1.6ms on the test dataset.