An Enhanced Algorithm for Detecting Blisters of Glass by Machine Vision
In this paper, we proposed image processing algorithms and developed the vision system for measuring blisters of flat glasses. The images captured by changing focus of camera because the depth of field of CCD camera is smaller than the depth of glasses and classified two types in blister as circle and ellipse types by the proposed criteria of measurement. We applied different methods to each type to improve the accuracy. In the pre-processing, it obtained binarized images to find blister. The information such as area, boundary, length, and position of blister has extracted from the binarized images by using chain code algorithm. For an illumination, the bright field illumination as back-light was applied. We tested the automatic measurement system, which we developed by using vision system, It successes 100% for detecting the blister at all glasses, and the error accuracy of information is about +/-10%.
Hyungsun Kim, JianFeng Yang, Tohru Sekino, Masakazu Anpo and Soo Wohn Lee
C. H. Han et al., "An Enhanced Algorithm for Detecting Blisters of Glass by Machine Vision", Materials Science Forum, Vol. 658, pp. 129-132, 2010