自动化学报Issue(8)：1667-1679,13.DOI:10.3724/SP.J.1004.2014.01667
基于反向P-M扩散的钢轨表面缺陷视觉检测
Research on Inverse P-M Diffusion-based Rail Surface Defect Detection
摘要
Abstract
A vision machine is developed for rail surface defects detection based on the inverse P-M (Perona-Malik) diffusion. The rail surface defects images can be obtained through an image acquisition system. The rail surface images show illumination variation, reflection inequality, and heterogeneous texture, they make the automated visual inspection task extremely difficult. The faultless region of the rail surface image is preserved by an inverse P-M model, but the fault region is smoothed after diffusing by an inverse P-M model. Therefore, by subtracting the inverse diffused image from the original image, the defects can be distinctly enhanced in the difference image. The influence of illumination variation, reflection inequality, and heterogeneous texture can also be decreased. A simple binary thresholding, followed by filter operations based on the edge performance and the size of defects, can then easily segment the defect. The simulation and field experiments indicate that the inspection machine can detect the rail surface defects effectively and the detection speed, accuracy, detection ratio and the fault ratio also satisfy the needs of automated rail track.关键词
反向P-M扩散/图像差分/钢轨表面缺陷/视觉检测Key words
Inverse P-M (Perona-Malik) diffusion/image difference/rail surface defects/vision detection引用本文复制引用
贺振东,王耀南,毛建旭,印峰..基于反向P-M扩散的钢轨表面缺陷视觉检测[J].自动化学报,2014,(8):1667-1679,13.基金项目
国家自然科学基金(60835004,61072121,61172160,61175075),河南省科技攻关计划(142102210514)资助Supported by National Natural Science Foundation of China (60835004,61072121,61172160,61175075), and the Key Science and Technology Program of Henan Province (142102210514) （60835004,61072121,61172160,61175075）
