期刊论文详细信息
IEEE Access
Automatic Detection of Dispersed Defects in Resin Eyeglass Based on Machine Vision Technology
Wei Ding1  Qingguo Wang2  Jianfeng Zhu3 
[1] Faculty of Electrical Engineering and Automation, Changshu Institute of Technology, Changshu, China;Faculty of Engineering and the Built Environment, Institute for Intelligent Systems, University of Johannesburg, Johannesburg, South Africa;School of Mechanical Engineering, Jiangsu University, Zhenjiang, China;
关键词: Automatic detection;    dispersed defects;    imaging analysis;    machine vision;    resin eyeglass;   
DOI  :  10.1109/ACCESS.2020.2978001
来源: DOAJ
【 摘 要 】

This paper is concerned with detection of dispersed defects in the resin eyeglass. At present, manual detection is always used in industry, which inevitably causes impairing eyes and a high rate of false-negative detection. Statistics show that its average accuracy and the average detection time are about 85% and 10s, respectively. We for the first time propose an automatic approach to detection of dispersed defects in resin eyeglass, based on the machine vision technology. It is observed that the refractivity of the normal and the defective regions of an eyeglass are different, and thus the reflection image is also collected in our system in addition to the normal transmission image. Such an optical imaging system is modelled and its analysis shows the gray-scale gradient difference between the normal and defective regions in the acquired image is dramatically enhanced under the illumination of a point light source with our designed system. An image processing algorithm is then developed to reveal the above difference and detect dispersed defects in resin eyeglasses. Our simulation study verifies the proposed approach. Further, its experimental evaluation was carried out and the result was consistent with the simulation one, showing that its detection accuracy and the average detection time were 97.50% and 0.636s, respectively, which meet the requirements for online detection of dispersed defects.

【 授权许可】

Unknown   

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