基于机器视觉的光学薄膜表面缺陷在线检测系统

On-line Detection System of Optical Thin FilmSurface Defects Based on Machine Vision

传统人工检测难以同时满足光学薄膜缺陷检测速度要求高、缺陷种类多、缺陷尺寸变化大等特点,为此提出了一种基于机器视觉的自动化在线检测系统,给出了一种高效可行的满足光学薄膜在线检测的算法流程。对原始图像使用改进的均值滤波器进行预处理之后,采用基于Otsu阈值分割算法实现薄膜缺陷的快速精确分割,提高薄膜缺陷特征提取和识别的效率及精度。使用漏检率和误检率两个指标进行相应的实验,结果表明,该系统高效可行。在最大检测速度300m/min时,漏检率和误检率分别为4.6%和4.8%,符合企业生产要求。

The traditional manual detection is difficult to meet the requirements of high speed,many kinds of defects and large change of defect size of optical thin film defect detection.Therefore,an automatic online detection system based on machine vision is proposed,and an efficient and feasible algorithm flow to meet the online detection of optical thin films is given.After preprocessing the original image with the improved mean filter,the Otsu threshold segmentation algorithm is used to achieve fast and accurate segmentation of thin film defects,which improves the efficiency and accuracy of thin film defect feature extraction and recognition.The corresponding experiments were carried out by using the false detection rate and missed detection rate,and the results show that the system is efficient and feasible.At the maximum detection speed of 300 m/min,the missed detection rate and false detection rate are 4.6%and 4.8%,respectively,which meet the production requirements of enterprises.