中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Adaptive Visual Inspection Method for Transparent Label Defect Detection of Curved Glass Bottle

文献类型:会议论文

作者Gong, Wei1; Zhang, Kunbo2; Yang, Chengwu3; Yi, Mingdong1; Wu, Jun1,4
出版日期2020-11-30
会议日期10-12 July 2020
会议地点Chongqing, China
DOI10.1109/CVIDL51233.2020.00024
英文摘要

Automatic visual inspection of transparent materials has always been a challenging issue in industry due to complicated interference from reflection and refraction. In this paper, we present a study of machine vision system for automatic online inspection of transparent label defect on curved glass bottle. An area-array camera and a custom-made blue dome illumination device are introduced to capture high quality standstill image by eliminating reflection. To overcome the distortion issue on curved geometry shape, we have introduced the deformable template matching method for accurate location. An adaptive threshold selection strategy is proposed to effectively detect small scratch by using global and local threshold values together with Gaussian fitting algorithm. Considering the golden edge printing error, skeleton extraction and distance transformation are applied to detect the whole edge contour of Chinese characters with special font. Our visual inspection system has been deployed in a glass bottle manufacturing plant for on-line quality control. Field test result demonstrates that the detection accuracy reaches 99.5% at a speed of 60 pc/min for over 60,000 bottles.

语种英语
URL标识查看原文
源URL[http://ir.ia.ac.cn/handle/173211/45476]  
专题自动化研究所_智能感知与计算研究中心
作者单位1.Qilu University of Technology
2.Institute of Automation, Chinese Academy of Sciences
3.Tianjin Academy for Intelligent Recognition Technologies
4.Sichuan Provincial Machinery Research and Design Institute
推荐引用方式
GB/T 7714
Gong, Wei,Zhang, Kunbo,Yang, Chengwu,et al. Adaptive Visual Inspection Method for Transparent Label Defect Detection of Curved Glass Bottle[C]. 见:. Chongqing, China. 10-12 July 2020.

入库方式: OAI收割

来源:自动化研究所

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