基于改进差分图像法的手机屏幕缺陷检测

Jianguo Zhang, Ying Li, Chunmei Zuo, Mingxing Xing
{"title":"基于改进差分图像法的手机屏幕缺陷检测","authors":"Jianguo Zhang, Ying Li, Chunmei Zuo, Mingxing Xing","doi":"10.1109/ICIIBMS46890.2019.8991460","DOIUrl":null,"url":null,"abstract":"The defect inspection with machine vision plays an important role in the quality control of mobile phone screen manufacturing. An improved difference image method is proposed to detect the defects of mobile phone screen. Considering the problem of misalignment of mobile phone screen image, PatMax algorithm and image correction technology based on affine transform are adopted to realize pixel alignment between template image and testing image. With the intention of eliminating noise effects and protecting the edge information of the test image, a image filtering is performed by 3×3 median filtering. Based on the above image preprocessing results, the defect-free image is used as the template image and the fuzzy processing is carried out, the differential operational between the testing image and the template image is performed to obtain the residual image, and the improved Otsu dual threshold method is used to achieve defect judgment on residual images. The experimental results show that the approach proposed in this study has achieved high efficiency and accuracy.","PeriodicalId":444797,"journal":{"name":"2019 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Defect detection of mobile phone screen based on improved difference image method\",\"authors\":\"Jianguo Zhang, Ying Li, Chunmei Zuo, Mingxing Xing\",\"doi\":\"10.1109/ICIIBMS46890.2019.8991460\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The defect inspection with machine vision plays an important role in the quality control of mobile phone screen manufacturing. An improved difference image method is proposed to detect the defects of mobile phone screen. Considering the problem of misalignment of mobile phone screen image, PatMax algorithm and image correction technology based on affine transform are adopted to realize pixel alignment between template image and testing image. With the intention of eliminating noise effects and protecting the edge information of the test image, a image filtering is performed by 3×3 median filtering. Based on the above image preprocessing results, the defect-free image is used as the template image and the fuzzy processing is carried out, the differential operational between the testing image and the template image is performed to obtain the residual image, and the improved Otsu dual threshold method is used to achieve defect judgment on residual images. The experimental results show that the approach proposed in this study has achieved high efficiency and accuracy.\",\"PeriodicalId\":444797,\"journal\":{\"name\":\"2019 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIIBMS46890.2019.8991460\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIIBMS46890.2019.8991460","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

机器视觉缺陷检测在手机屏幕制造质量控制中起着重要的作用。提出了一种改进的差分图像检测手机屏幕缺陷的方法。针对手机屏幕图像的不对齐问题,采用PatMax算法和基于仿射变换的图像校正技术,实现模板图像与测试图像的像素对齐。为了消除噪声影响和保护测试图像的边缘信息,通过3×3中值滤波对图像进行滤波。在上述图像预处理结果的基础上,将无缺陷图像作为模板图像并进行模糊处理,对测试图像与模板图像进行差分运算得到残差图像,并采用改进的Otsu双阈值法对残差图像进行缺陷判断。实验结果表明,该方法具有较高的效率和准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Defect detection of mobile phone screen based on improved difference image method
The defect inspection with machine vision plays an important role in the quality control of mobile phone screen manufacturing. An improved difference image method is proposed to detect the defects of mobile phone screen. Considering the problem of misalignment of mobile phone screen image, PatMax algorithm and image correction technology based on affine transform are adopted to realize pixel alignment between template image and testing image. With the intention of eliminating noise effects and protecting the edge information of the test image, a image filtering is performed by 3×3 median filtering. Based on the above image preprocessing results, the defect-free image is used as the template image and the fuzzy processing is carried out, the differential operational between the testing image and the template image is performed to obtain the residual image, and the improved Otsu dual threshold method is used to achieve defect judgment on residual images. The experimental results show that the approach proposed in this study has achieved high efficiency and accuracy.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信