Xin Lu, Junying Jia, Zhiwei Pei, Daolin Wang, Jialin Wang, Bo Sun
{"title":"基于机器视觉的蓝牙耳机表面缺陷检测方法*","authors":"Xin Lu, Junying Jia, Zhiwei Pei, Daolin Wang, Jialin Wang, Bo Sun","doi":"10.1109/CSE53436.2021.00010","DOIUrl":null,"url":null,"abstract":"The surface defect detection technology of irregular object based on machine vision has been widely used in various industrial scenarios in recent years. In this paper, we take Bluetooth headsets as an example, propose a Bluetooth headset surface defect detection method. Based on the analysis of the surface characteristics and defects types of Bluetooth headset, the scratch and glue-overflowed problem on the surface of the headset are accurately detected. The experimental results shows that the detection algorithm can quickly and effectively detect the surface defects of Bluetooth headset, and the accuracy of defect recognition reaches 98%. Therefore, the detection algorithm has a certain practical application value in industry.","PeriodicalId":6838,"journal":{"name":"2021 IEEE 24th International Conference on Computational Science and Engineering (CSE)","volume":"13 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Method of Surface Defect Detection of Bluetooth Headset Based on Machine Vision*\",\"authors\":\"Xin Lu, Junying Jia, Zhiwei Pei, Daolin Wang, Jialin Wang, Bo Sun\",\"doi\":\"10.1109/CSE53436.2021.00010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The surface defect detection technology of irregular object based on machine vision has been widely used in various industrial scenarios in recent years. In this paper, we take Bluetooth headsets as an example, propose a Bluetooth headset surface defect detection method. Based on the analysis of the surface characteristics and defects types of Bluetooth headset, the scratch and glue-overflowed problem on the surface of the headset are accurately detected. The experimental results shows that the detection algorithm can quickly and effectively detect the surface defects of Bluetooth headset, and the accuracy of defect recognition reaches 98%. Therefore, the detection algorithm has a certain practical application value in industry.\",\"PeriodicalId\":6838,\"journal\":{\"name\":\"2021 IEEE 24th International Conference on Computational Science and Engineering (CSE)\",\"volume\":\"13 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 24th International Conference on Computational Science and Engineering (CSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSE53436.2021.00010\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 24th International Conference on Computational Science and Engineering (CSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSE53436.2021.00010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Method of Surface Defect Detection of Bluetooth Headset Based on Machine Vision*
The surface defect detection technology of irregular object based on machine vision has been widely used in various industrial scenarios in recent years. In this paper, we take Bluetooth headsets as an example, propose a Bluetooth headset surface defect detection method. Based on the analysis of the surface characteristics and defects types of Bluetooth headset, the scratch and glue-overflowed problem on the surface of the headset are accurately detected. The experimental results shows that the detection algorithm can quickly and effectively detect the surface defects of Bluetooth headset, and the accuracy of defect recognition reaches 98%. Therefore, the detection algorithm has a certain practical application value in industry.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
