LAUSR

Abstract In order to solve the problems of false detection and missed detection on punched steel strip brought by manual inspection, a machine vision detection system for nickel plated punched steel strip is built, from which a defect detection method of nickel-plated punched steel strip based on improved least square method is presented. At first, the image is extracted and preprocessed in order to obtain clear edge images. Then state transition algorithm and iterative algorithm are used to improve least square method. The iterative algorithm is used to obtain the data set of the center coordinates and the radius of the fitted circle. While the state transition algorithm is used to perform the optimization of the results after multiple iterations to obtain the optimal solution of the center and radius parameters. Finally, the parameters such as hole diameter, transverse hole distance and longitudinal hole distance are calculated and used to realize the defect detection. The experimental results show that the method proposed can realize the parameters calculation with an absolute error of less than 10um. It also can realize defect detection of the blind hole and connecting hole for nickel plated punched steel strip.