基于机器视觉的导光板缺陷检测方法研究

导光板在无尘车间制造过程中,因现场环境以及 生产治具的影响,不可避免的出现各种各样的缺 陷,造成产品质量的严重下降。针对这种问题,根据导光板的光学特性、缺陷形成原理及特 征,本文提出 一种基于机器视觉的导光板缺陷检测的方法。首先,根据导光板的导光点分布特性,提出了 基于密度的自 动分区算法；其次,针对不同分区,分别设计一个高斯双方向导数滤波器对导光板图像进行 卷积操作,并 利用在两个大小不一的均值滤波基础上做差,以去除正常导光点的干扰,获得缺陷增强图像 ；进而,利用 二值化阈值操作提取疑似缺陷连通区域,并在分析其区域特征基础上确认是否为缺陷,再加 以分类；最 后,在工业现场采集的导光板图像基础上,进行了大量的实验。实验结果表明,针对亮点、 压伤和线刮伤 缺陷具有较高的检测精度,基本可以满足工业检测要求。

Research on detecting method of light guide plate defect based on machine vision

According to the optical characteristics,defect formation mechamism and characte ristics of the light guide plate,this paper proposes a method of the defect dete ction based on machine vision.Firstly,according to the distribution characteri stics of the light guide points in the light guide plate,an automatic density-based partitioning algorithm is proposed.Secondly,a Gaussia n bidirectional guide filter is respectively designed to convolve the image of the light guide plate for differe nt partitions.Differences between the different sizes of the average filter are used to remove the interference from t he normal light guide points to obtain the defect-enhanced image.Then,the binarized threshold operation is used to e xtract the connected regions of the suspected defects.The final result is based on the analysis of its regional cha racteristics,which will be classified. Finally,a large number of experiments were carried out on the basis of the ligh t guide plate images collected in the industrial field.The experimental results show that the detection accuracy is hi gh for bright spot,compressi on and line scratch defects.It can basically meet the requirements of industrial detection.