{"title":"改进阈值分割在颜色绒毛检测中的应用","authors":"Hongze Xiao, Liqing Li, J. Wang, Shuhuai Huo","doi":"10.1109/CISP-BMEI.2017.8302073","DOIUrl":null,"url":null,"abstract":"This paper proposes an improved threshold segmentation to turn the image of fluffs into binary image, the noises and impurities in the image are eliminated by using Gauss filtering and the method of features statistics of color fluffs, then the centroid coordinate of each color fluff is calculated and the location information of each color fluff is obtained, finally every color fluff is detected and eliminated. The experiment proved that the threshold segmentation has the characteristics of high detection rate and fast calculate speed.","PeriodicalId":6474,"journal":{"name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"5 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The application of improved threshold segmentation on detection of color fluff\",\"authors\":\"Hongze Xiao, Liqing Li, J. Wang, Shuhuai Huo\",\"doi\":\"10.1109/CISP-BMEI.2017.8302073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an improved threshold segmentation to turn the image of fluffs into binary image, the noises and impurities in the image are eliminated by using Gauss filtering and the method of features statistics of color fluffs, then the centroid coordinate of each color fluff is calculated and the location information of each color fluff is obtained, finally every color fluff is detected and eliminated. The experiment proved that the threshold segmentation has the characteristics of high detection rate and fast calculate speed.\",\"PeriodicalId\":6474,\"journal\":{\"name\":\"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)\",\"volume\":\"5 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISP-BMEI.2017.8302073\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP-BMEI.2017.8302073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The application of improved threshold segmentation on detection of color fluff
This paper proposes an improved threshold segmentation to turn the image of fluffs into binary image, the noises and impurities in the image are eliminated by using Gauss filtering and the method of features statistics of color fluffs, then the centroid coordinate of each color fluff is calculated and the location information of each color fluff is obtained, finally every color fluff is detected and eliminated. The experiment proved that the threshold segmentation has the characteristics of high detection rate and fast calculate speed.
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