H. Kayaba, H. Takauji, S. Kaneko, M. Toda, Kouji Kuno, H. Suganuma
{"title":"Defect inspection system by dot data","authors":"H. Kayaba, H. Takauji, S. Kaneko, M. Toda, Kouji Kuno, H. Suganuma","doi":"10.1109/ISOT.2009.5326122","DOIUrl":null,"url":null,"abstract":"We successfully develop a defect inspection method based on a robust method for matching the distance between points in three dimensions. The three-dimensional distance data of an object is measured by means of a laser range finder. The data is compared with the measured data of a high-quality item. Then, we examine the differences between two sets of data in order to detect defects in the target object. The three-dimensional distance data is matched with high robustness by using the proposed method. Furthermore, we attach labels to sets of points corresponding to a detected defect. By performing an experiment with real data, we show that a high-quality object and a defect object can be distinguished on the basis of the features of each label.","PeriodicalId":366216,"journal":{"name":"2009 International Symposium on Optomechatronic Technologies","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Symposium on Optomechatronic Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISOT.2009.5326122","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We successfully develop a defect inspection method based on a robust method for matching the distance between points in three dimensions. The three-dimensional distance data of an object is measured by means of a laser range finder. The data is compared with the measured data of a high-quality item. Then, we examine the differences between two sets of data in order to detect defects in the target object. The three-dimensional distance data is matched with high robustness by using the proposed method. Furthermore, we attach labels to sets of points corresponding to a detected defect. By performing an experiment with real data, we show that a high-quality object and a defect object can be distinguished on the basis of the features of each label.