{"title":"Pattern segmentation in textile images","authors":"Andreea Smoaca, D. Coltuc, V. Lazarescu","doi":"10.1109/ISSCS.2009.5206185","DOIUrl":null,"url":null,"abstract":"This paper presents some results regarding the automatic segmentation of patterns in images of textile samples. The pattern segmentation is necessary for further extraction of a set of shape descriptors to be used in a CBIR database for textiles. Five different filters for removing the fabrics texture have been tested: mean, median, Gaussian, soft wavelet thresholding and a new approach based on Wavelet Transform and Independent Components Analysis. For segmentation, due to the poor color content of the images, the binarization proved to be a satisfactory choice. Three algorithms for the threshold computation have been tested: Otsu, background symmetry and triangle.","PeriodicalId":277587,"journal":{"name":"2009 International Symposium on Signals, Circuits and Systems","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Symposium on Signals, Circuits and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSCS.2009.5206185","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper presents some results regarding the automatic segmentation of patterns in images of textile samples. The pattern segmentation is necessary for further extraction of a set of shape descriptors to be used in a CBIR database for textiles. Five different filters for removing the fabrics texture have been tested: mean, median, Gaussian, soft wavelet thresholding and a new approach based on Wavelet Transform and Independent Components Analysis. For segmentation, due to the poor color content of the images, the binarization proved to be a satisfactory choice. Three algorithms for the threshold computation have been tested: Otsu, background symmetry and triangle.
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