文献类型：会议论文

英文题名：Research on distortion correction of particleboard surface defect image

作者：Zhao, Ziyu[1] Guo, Hui[2] Yang, Xiaoxia[1] Ge, Zhedong[1] Zhou, Yucheng[1,2]

第一作者：Zhao, Ziyu

通信作者：Zhao, Z.[1]

机构：[1] School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan, China; [2] Research Institute of Wood Industry, Chinese Academy of Forestry, Beijing, China

会议论文集：Proceeding of PRIS 2021 - 2021 3rd International Conference on Pattern Recognition and Intelligent Systems

会议日期：July 28, 2021 - July 30, 2021

会议地点：Virtual, Online, Thailand

语种：英文

外文关键词：Calibration - Image enhancement - Particle board - Surface defects - Visualization

年份：2021

摘要：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. ? 2021 ACM.