{"title":"一种改进的羊绒、羊毛纤维图像分水岭变换方法","authors":"Shuyuan Shang, Ya-Xia Liu, Fei-Fei Meng","doi":"10.1109/ICMLC.2012.6359526","DOIUrl":null,"url":null,"abstract":"Through the experiment, if using the traditional watershed algorithm of cashmere image edge extraction, the results will appear serious `over-segmentation' phenomenon. This paper adopts multi-resolution analysis theory, using wavelet transformation theory establishment multi-resolution analysis framework on image segmentation. Multi-wavelet transform has some unique advantages and good performance on edge detection and texture analysis. This research uses multi-wavelet transform to improve the over-segmentation watershed transformation, to get meaningful image segmentation result. It facilitates the preparation for the extraction of characteristic such as cashmere image diameter, flake highly, and etc.","PeriodicalId":128006,"journal":{"name":"2012 International Conference on Machine Learning and Cybernetics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An improved method of watershed transform on image of cashmere and wool fibre\",\"authors\":\"Shuyuan Shang, Ya-Xia Liu, Fei-Fei Meng\",\"doi\":\"10.1109/ICMLC.2012.6359526\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Through the experiment, if using the traditional watershed algorithm of cashmere image edge extraction, the results will appear serious `over-segmentation' phenomenon. This paper adopts multi-resolution analysis theory, using wavelet transformation theory establishment multi-resolution analysis framework on image segmentation. Multi-wavelet transform has some unique advantages and good performance on edge detection and texture analysis. This research uses multi-wavelet transform to improve the over-segmentation watershed transformation, to get meaningful image segmentation result. It facilitates the preparation for the extraction of characteristic such as cashmere image diameter, flake highly, and etc.\",\"PeriodicalId\":128006,\"journal\":{\"name\":\"2012 International Conference on Machine Learning and Cybernetics\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Machine Learning and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLC.2012.6359526\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Machine Learning and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2012.6359526","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An improved method of watershed transform on image of cashmere and wool fibre
Through the experiment, if using the traditional watershed algorithm of cashmere image edge extraction, the results will appear serious `over-segmentation' phenomenon. This paper adopts multi-resolution analysis theory, using wavelet transformation theory establishment multi-resolution analysis framework on image segmentation. Multi-wavelet transform has some unique advantages and good performance on edge detection and texture analysis. This research uses multi-wavelet transform to improve the over-segmentation watershed transformation, to get meaningful image segmentation result. It facilitates the preparation for the extraction of characteristic such as cashmere image diameter, flake highly, and etc.