{"title":"Automatic image processing filter generation for visual defects classification system","authors":"S. Hata, J. Hayashi","doi":"10.1109/ICMECH.2009.4957119","DOIUrl":null,"url":null,"abstract":"The visual inspection system is used in various production systems. The Visual Inspection System is used to maintain the quality of products. But, there are some defects which are not detected with enough reliability on conventional systems. To meet with the problems, the automatic generation system of best image processing filters which extract the proper characteristics of images for that kind of defects has been introduced to improve recognition rate. The system is designed to generate two kinds of filters to detect the defects with vague edge and widely distributed defect images using neural network method and co-occurrence histogram images. Experiments shows the generated filters get better recognition rate.","PeriodicalId":414967,"journal":{"name":"2009 IEEE International Conference on Mechatronics","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Mechatronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMECH.2009.4957119","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
The visual inspection system is used in various production systems. The Visual Inspection System is used to maintain the quality of products. But, there are some defects which are not detected with enough reliability on conventional systems. To meet with the problems, the automatic generation system of best image processing filters which extract the proper characteristics of images for that kind of defects has been introduced to improve recognition rate. The system is designed to generate two kinds of filters to detect the defects with vague edge and widely distributed defect images using neural network method and co-occurrence histogram images. Experiments shows the generated filters get better recognition rate.
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