Automatic detection of watermask for resin glasses by machine vision
1. School of Mechanical Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China; 2. School of Food and Biological Engineering, Jiangsu University, Zhenjiang, Jiangsu, 212013, China
Abstract：To realize the automatic detection of watermask for resin glasses, the point light projection illumination model was built to explore the influence factors of relative distance between light source and resin glasses, imaging screen reflectivity, glasses physical properties and imaging distance on the imaging. Based on the simulation result, the automatic detection system for watermask was designed to capture and analyze the projection image. The algorithms of region growing, morphological operation and ellipsefitting were employed to segment the glasses projection region from the background. Sobel edge detection and thresholding were combined to extract the region with sudden change of grayscale in local pixel space. The connected region area was calculated and served as constraint condition for further selection of the defect region. The experimental results show that the digital image process can be applied to different type of resin glasses. The recognition of glasses watermask can reach 100%, and the process of imaging, recognition and location consumes 872 ms.
孙力, 刘晨, 姚红兵. 基于机器视觉的树脂镜片水印疵病检测[J]. 江苏大学学报（自然科学版）, 2018, 39(4): 425-430.
SUN Li, LIU Chen, YAO Hong-Bing. Automatic detection of watermask for resin glasses by machine vision[J]. Journal of Jiangsu University(Natural Science Eidtion)
, 2018, 39(4): 425-430.
2018, Vol. 39 
