{"title":"基于中轴和对称信息的骨架化","authors":"Yung-Sheng Chen, Ming-Te Chao","doi":"10.1109/ICMLC.2012.6359609","DOIUrl":null,"url":null,"abstract":"The classical and potential thinning issues such as bias effect, boundary noise immunity, and even rotation invariant, are quite worthy of studying in image processing field. In this paper, based on the fundamental medial axis transformation (MAT) concept, we developed an approach including extraction of medial axis with symmetry information, clustering, linking, and post rule-based thinning to investigate the possibility of reducing the bias effect and increasing the boundary noise immunity. A rotation invariant rule-based thinning algorithm was adopted for experimental comparisons. The primary result confirms that the proposed approach is one of the feasible directions to overcome these issues.","PeriodicalId":128006,"journal":{"name":"2012 International Conference on Machine Learning and Cybernetics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Skeletonization based on the medial-axis and symmetry information\",\"authors\":\"Yung-Sheng Chen, Ming-Te Chao\",\"doi\":\"10.1109/ICMLC.2012.6359609\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The classical and potential thinning issues such as bias effect, boundary noise immunity, and even rotation invariant, are quite worthy of studying in image processing field. In this paper, based on the fundamental medial axis transformation (MAT) concept, we developed an approach including extraction of medial axis with symmetry information, clustering, linking, and post rule-based thinning to investigate the possibility of reducing the bias effect and increasing the boundary noise immunity. A rotation invariant rule-based thinning algorithm was adopted for experimental comparisons. The primary result confirms that the proposed approach is one of the feasible directions to overcome these issues.\",\"PeriodicalId\":128006,\"journal\":{\"name\":\"2012 International Conference on Machine Learning and Cybernetics\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Machine Learning and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLC.2012.6359609\",\"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.2012.6359609","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Skeletonization based on the medial-axis and symmetry information
The classical and potential thinning issues such as bias effect, boundary noise immunity, and even rotation invariant, are quite worthy of studying in image processing field. In this paper, based on the fundamental medial axis transformation (MAT) concept, we developed an approach including extraction of medial axis with symmetry information, clustering, linking, and post rule-based thinning to investigate the possibility of reducing the bias effect and increasing the boundary noise immunity. A rotation invariant rule-based thinning algorithm was adopted for experimental comparisons. The primary result confirms that the proposed approach is one of the feasible directions to overcome these issues.