Felipe S. Farias, Waldir Sabino da Silva, E. B. D. L. Filho, W. Melo
{"title":"Automated content detection on TVs and computer monitors","authors":"Felipe S. Farias, Waldir Sabino da Silva, E. B. D. L. Filho, W. Melo","doi":"10.1109/GCCE.2015.7398693","DOIUrl":null,"url":null,"abstract":"In a system manufacturing process that use screens, for exemple, TVs, computer monitors, or notebook, the inspection images is one of the most important quality tests. Due to increasing complexity of these systems, manual inspection became complex and slow. Thus, automatic inspection is an attractive alternative. In this paper, we present an automatic inspection system images using edge and line detection algorithms, rectangles recognition and image comparison metrics. The experiments, performed to 504 images (TVs, computer monitors, and notebook) demonstrate that the system has good performance.","PeriodicalId":363743,"journal":{"name":"2015 IEEE 4th Global Conference on Consumer Electronics (GCCE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 4th Global Conference on Consumer Electronics (GCCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GCCE.2015.7398693","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In a system manufacturing process that use screens, for exemple, TVs, computer monitors, or notebook, the inspection images is one of the most important quality tests. Due to increasing complexity of these systems, manual inspection became complex and slow. Thus, automatic inspection is an attractive alternative. In this paper, we present an automatic inspection system images using edge and line detection algorithms, rectangles recognition and image comparison metrics. The experiments, performed to 504 images (TVs, computer monitors, and notebook) demonstrate that the system has good performance.