Research on distortion correction of particleboard surface defect image

Abstract

In order to improve the barrel distortion of the acquired image in the surface defect detection of particleboard. In this paper, a method based on Zhang Zhengyou calibration is used to solve the camera distortion problem, so as to improve the accuracy of surface defect image processing of particleboard. Firstly, the camera was calibrated, and then the improvement of the camera correction information accuracy was judged by the correction of external parameters and reprojection error of image visualization. The internal parameter matrix and distortion coefficient of the camera were calculated accurately, and the barrel distortion of the image was corrected finally. The position of the inner corner points detected by the camera is accurate, and the reprojected points were included in the inner corner points, which improves the correction accuracy of the image to be measured. It can be clearly seen from the external parameters of visualization that the placement of the 16 sample patterns is within the range of vision. The oblique Angle deviation between the images is within 150mm. The average value of the re projection error was 0.1570 pixels calculated by the point of the camera re projection, which meets the need of correction. In conclusion, the image quality can be improved by accurately correcting the distortion of particleboard image. It lays a foundation for the surface defect extraction of particleboard.