图像处理技术的光学元件表面疵病检测  

Surface defect detection of optical elements based on image processing technology

作　　者：丁兵兵 匡珍春[2] 王军民 何小山 DING Bingbing;KUANG Zhenchun;WANG Junmin;HE Xiaoshan(Zhanjiang Science and Technology College,Zhanjiang Guangdong 524094,China;Guangdong Ocean University,Zhanjiang Guangdong 524088,China)

机构地区：[1]湛江科技学院智能制造学院,广东湛江524094 [2]广东海洋大学数学与计算机学院,广东湛江524088

出　　处：《激光杂志》2022年第11期31-35,共5页Laser Journal

基　　金：国家自然科学基金青年科学基金(No.51208118);湛江科技学院2019年校级大学生创新创业训练计划项目(No.2020CJXYDCZD02)。

摘　　要：提出基于图像处理技术的光学元件表面疵病检测方法,旨在提高光学元件表面疵病检测精度。采用背景校正算法去除图像噪声并均匀补偿背景,通过的自适应阈值法分割疵病目标区域,结合图像梯度信息,改善最大类间方差法局限性,使用外接矩形法刻画分割得到疵病目标区域尺寸,实现光学元件表面疵病检测。实验证明:该方法校正后的疵病图像背景均匀性较好,且未出现图像细节大量丢失情况,抗噪能力强;能够判断疵病形状,划分麻点和划痕类疵病,光学元件表面疵病检测效果好。An optical element surface defect detection method based on image processing technology is proposed to improve the detection accuracy of optical element surface defects. The background correction algorithm is used to remove the image noise and compensate the background evenly. The defect target area is segmented by the adaptive threshold method. Combined with the image gradient information, the limitation of the maximum interclass variance method is improved. The size of the defect target area is obtained by the circumscribed rectangle method, and the surface defect detection of optical elements is realized. Experiments show that the background uniformity of the defect image corrected by this method is good, there is no loss of a large number of image details, and the anti-noise ability is strong. It can judge the defect shape, divide pitting and scratch defects, and has good detection effect on the surface defects of optical elements.

关 键 词：图像处理技术 表面疵病 图像形态学 背景校正算法 

分 类 号：TN209[电子电信—物理电子学]