基于灰度及几何特征的微晶玻璃缺陷检测

Detection of defects in glass-ceramics based on grayscale and geometric features

气泡缺陷检测作为评估微晶玻璃材料性能的重要环节,可指导微晶玻璃原坯切割与再加工,充分发挥其稳定的光学特性。针对环形光源照射微晶玻璃圆柱试样时,视场背景亮度不均匀且微晶玻璃外周边界被增亮的问题,提出了一种基于灰度及几何特征的微晶玻璃气泡检测算法。算法先根据图像局部灰度特征利用Canny边缘检测算子获取疑似气泡轮廓,再基于气泡几何特征剔除微晶玻璃外周边界的虚假目标获得真实气泡缺陷信息。实验结果表明该算法能有效提取气泡缺陷,提高气泡缺陷检测准确率。

As an important part of evaluating the performance of glass-ceramic materials, bubble defect detection can guide the cutting and reprocessing of the original glass-ceramics to give full play to its stable optical characteristics. Due to the problem that the background brightness of the field of view is uneven and the outer periphery of the glass-ceramic is brightened when the circular light source illuminates the cylindrical glass-ceramic, a glass-ceramic bubble detection algorithm based on grayscale and geometric characteristics is introduced. Possible bubble outlines are obtained by Canny edge detection according to the local image gray feature, and then the false outlines are removed according to bubble geometric characteristics to obtain the real bubble defect information. Experimental results show that the algorithm can effectively extract bubble defects and improve the accuracy of bubble defect detection.