F. Gayubo, Jose Luis Navarro Gonzalez, Eusebio de la Fuente López, F. M. Trespaderne, J. Perán
{"title":"板料成形过程中劈裂缺陷在线检测的机器视觉系统","authors":"F. Gayubo, Jose Luis Navarro Gonzalez, Eusebio de la Fuente López, F. M. Trespaderne, J. Perán","doi":"10.1109/ICPR.2006.902","DOIUrl":null,"url":null,"abstract":"In this paper, we present an automatic system designed for detect the presence of split defects in sheet-metal forming processes. The image acquisition system includes basically a CCD progressive camera and a diffuse illumination system mounted on the end-effector of a 6-dof robot. The inspection-robot displaces the image acquisition system over the pieces proceeding from the sheet-metal forming line. The recognition, positioning and the later inspection are realized as the pieces are moving on a conveyor belt. To realize the inspection, the acquired images are restored using a Markov random field model. Defect detection is carried out using a valley detection algorithm. To realize the recognition and to determine the precise position, we have used an appearance-based method, based on a principal component analysis (PCA)","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":"{\"title\":\"On-line machine vision system for detect split defects in sheet-metal forming processes\",\"authors\":\"F. Gayubo, Jose Luis Navarro Gonzalez, Eusebio de la Fuente López, F. M. Trespaderne, J. Perán\",\"doi\":\"10.1109/ICPR.2006.902\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present an automatic system designed for detect the presence of split defects in sheet-metal forming processes. The image acquisition system includes basically a CCD progressive camera and a diffuse illumination system mounted on the end-effector of a 6-dof robot. The inspection-robot displaces the image acquisition system over the pieces proceeding from the sheet-metal forming line. The recognition, positioning and the later inspection are realized as the pieces are moving on a conveyor belt. To realize the inspection, the acquired images are restored using a Markov random field model. Defect detection is carried out using a valley detection algorithm. To realize the recognition and to determine the precise position, we have used an appearance-based method, based on a principal component analysis (PCA)\",\"PeriodicalId\":236033,\"journal\":{\"name\":\"18th International Conference on Pattern Recognition (ICPR'06)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"28\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"18th International Conference on Pattern Recognition (ICPR'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.2006.902\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"18th International Conference on Pattern Recognition (ICPR'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2006.902","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On-line machine vision system for detect split defects in sheet-metal forming processes
In this paper, we present an automatic system designed for detect the presence of split defects in sheet-metal forming processes. The image acquisition system includes basically a CCD progressive camera and a diffuse illumination system mounted on the end-effector of a 6-dof robot. The inspection-robot displaces the image acquisition system over the pieces proceeding from the sheet-metal forming line. The recognition, positioning and the later inspection are realized as the pieces are moving on a conveyor belt. To realize the inspection, the acquired images are restored using a Markov random field model. Defect detection is carried out using a valley detection algorithm. To realize the recognition and to determine the precise position, we have used an appearance-based method, based on a principal component analysis (PCA)