镜面反射
人工智能
计算机视觉
计算机科学
光学
对比度(视觉)
材料科学
分割
数码相机
物理
作者
Paulo M.F. Forte,Paulo Eduardo Reis Felgueiras,Flávio P. Ferreira,Marta Noronha e Sousa,Eduardo J. Nunes-Pereira,Boris P. J. Bret,M. Belsley
标识
DOI:10.1016/j.optlaseng.2016.08.002
摘要
An automatic optical inspection system for detecting local defects on specular surfaces is presented. The system uses an image display to produce a sequence of structured diffuse illumination patterns and a digital camera to acquire the corresponding sequence of images. An image enhancement algorithm, which measures the local intensity variations between bright- and dark-field illumination conditions, yields a final image in which the defects are revealed with a high contrast. Subsequently, an image segmentation algorithm, which compares statistically the enhanced image of the inspected surface with the corresponding image for a defect-free template, allows separating defects from non-defects with an adjusting decision threshold. The method can be applied to shiny surfaces of any material including metal, plastic and glass. The described method was tested on the plastic surface of a car dashboard system. We were able to detect not only scratches but also dust and fingerprints. In our experiment we observed a detection contrast increase from about 40%, when using an extended light source, to more than 90% when using a structured light source. The presented method is simple, robust and can be carried out with short cycle times, making it appropriate for applications in industrial environments.
科研通智能强力驱动
Strongly Powered by AbleSci AI