F. Bulnes, R. Usamentiaga, D. García, J. Molleda, J. Rendueles
{"title":"基于视觉的热轧带钢缺陷周期性检测技术","authors":"F. Bulnes, R. Usamentiaga, D. García, J. Molleda, J. Rendueles","doi":"10.1109/IAS.2011.6074384","DOIUrl":null,"url":null,"abstract":"This document presents a technique to detect a particularly serious problem: periodical defects. Periodical defects can cause serious damage to steel strips, and so should be corrected as quickly as possible. The technique proposed, which is based on information provided by an artificial vision system, reports on periodical defects detected in one strip before starting to roll the next.","PeriodicalId":268988,"journal":{"name":"2011 IEEE Industry Applications Society Annual Meeting","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Vision-based technique for periodical defect detection in hot steel strips\",\"authors\":\"F. Bulnes, R. Usamentiaga, D. García, J. Molleda, J. Rendueles\",\"doi\":\"10.1109/IAS.2011.6074384\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This document presents a technique to detect a particularly serious problem: periodical defects. Periodical defects can cause serious damage to steel strips, and so should be corrected as quickly as possible. The technique proposed, which is based on information provided by an artificial vision system, reports on periodical defects detected in one strip before starting to roll the next.\",\"PeriodicalId\":268988,\"journal\":{\"name\":\"2011 IEEE Industry Applications Society Annual Meeting\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE Industry Applications Society Annual Meeting\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IAS.2011.6074384\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE Industry Applications Society Annual Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAS.2011.6074384","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Vision-based technique for periodical defect detection in hot steel strips
This document presents a technique to detect a particularly serious problem: periodical defects. Periodical defects can cause serious damage to steel strips, and so should be corrected as quickly as possible. The technique proposed, which is based on information provided by an artificial vision system, reports on periodical defects detected in one strip before starting to roll the next.