{"title":"基于计算机视觉和人工神经网络的丝绸纹理缺陷识别系统","authors":"A. Oonsivilai, Nittaya Meeboon","doi":"10.1109/CISP.2009.5303972","DOIUrl":null,"url":null,"abstract":"Competiveness of textile industries depends on the quality control of production. In order to minimize production cost, effort is directed towards less defectiveness and time spent on production operations. More accuracy in silk texture defect identification should be maintained so as eliminate any abnormality in the silk texture that hinders its acceptability by the consumer. In this paper, silk texture defect identification is achieved by implementing artificial neural network (ANN) technique. Methodology for feature selection that leads to high recognition rates and to simpler classification systems architectures is presented. Keywords-silk texture; computer-vision; accuracy; artifitial neural network I. INTRODUCTION","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"76 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Silk Texture Defect Recognition System Using Computer Vision and Artificial Neural Networks\",\"authors\":\"A. Oonsivilai, Nittaya Meeboon\",\"doi\":\"10.1109/CISP.2009.5303972\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Competiveness of textile industries depends on the quality control of production. In order to minimize production cost, effort is directed towards less defectiveness and time spent on production operations. More accuracy in silk texture defect identification should be maintained so as eliminate any abnormality in the silk texture that hinders its acceptability by the consumer. In this paper, silk texture defect identification is achieved by implementing artificial neural network (ANN) technique. Methodology for feature selection that leads to high recognition rates and to simpler classification systems architectures is presented. Keywords-silk texture; computer-vision; accuracy; artifitial neural network I. INTRODUCTION\",\"PeriodicalId\":263281,\"journal\":{\"name\":\"2009 2nd International Congress on Image and Signal Processing\",\"volume\":\"76 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 2nd International Congress on Image and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISP.2009.5303972\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd International Congress on Image and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP.2009.5303972","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Silk Texture Defect Recognition System Using Computer Vision and Artificial Neural Networks
Competiveness of textile industries depends on the quality control of production. In order to minimize production cost, effort is directed towards less defectiveness and time spent on production operations. More accuracy in silk texture defect identification should be maintained so as eliminate any abnormality in the silk texture that hinders its acceptability by the consumer. In this paper, silk texture defect identification is achieved by implementing artificial neural network (ANN) technique. Methodology for feature selection that leads to high recognition rates and to simpler classification systems architectures is presented. Keywords-silk texture; computer-vision; accuracy; artifitial neural network I. INTRODUCTION