{"title":"基于多尺度马尔科夫随机场的织物图像分割","authors":"Ruilin Zhang, Yan Hu, W. Guo, Chenyan Zhang","doi":"10.1109/ISCID.2009.148","DOIUrl":null,"url":null,"abstract":"To recognize the organizational structure of fabrics effectively, a fabric image segmentation method based on multi-scale Markov random field (MRF) was presented. Multi-scale MRF was applied to segment fabric images combined with edge information, which is extracted by the modulus maximum of wavelet transform. Experimental results show that the segmentation algorithm associated with edge information can reduce the computing time and most misclassifications. So, the approach is feasible and effective for fabric image segmentation.","PeriodicalId":294370,"journal":{"name":"International Symposium on Computational Intelligence and Design","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Multi-scale Markov Random Field Based Fabric Image Segmentation Associate with Edge Information\",\"authors\":\"Ruilin Zhang, Yan Hu, W. Guo, Chenyan Zhang\",\"doi\":\"10.1109/ISCID.2009.148\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To recognize the organizational structure of fabrics effectively, a fabric image segmentation method based on multi-scale Markov random field (MRF) was presented. Multi-scale MRF was applied to segment fabric images combined with edge information, which is extracted by the modulus maximum of wavelet transform. Experimental results show that the segmentation algorithm associated with edge information can reduce the computing time and most misclassifications. So, the approach is feasible and effective for fabric image segmentation.\",\"PeriodicalId\":294370,\"journal\":{\"name\":\"International Symposium on Computational Intelligence and Design\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposium on Computational Intelligence and Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCID.2009.148\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Computational Intelligence and Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCID.2009.148","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-scale Markov Random Field Based Fabric Image Segmentation Associate with Edge Information
To recognize the organizational structure of fabrics effectively, a fabric image segmentation method based on multi-scale Markov random field (MRF) was presented. Multi-scale MRF was applied to segment fabric images combined with edge information, which is extracted by the modulus maximum of wavelet transform. Experimental results show that the segmentation algorithm associated with edge information can reduce the computing time and most misclassifications. So, the approach is feasible and effective for fabric image segmentation.