{"title":"基于边缘和区域属性的多尺度自适应分割","authors":"B. McCane, T. Caelli","doi":"10.1109/KES.1997.616854","DOIUrl":null,"url":null,"abstract":"The authors present an adaptive multi-scale algorithm using edge and region information for segmenting intensity images into closed regions. The need for segmentation is determined by region statistics and segmentation is actually performed using edge based information. Results are shown for a number of images displaying significant improvements over mono-scale segmentation.","PeriodicalId":166931,"journal":{"name":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Multi-scale adaptive segmentation using edge and region based attributes\",\"authors\":\"B. McCane, T. Caelli\",\"doi\":\"10.1109/KES.1997.616854\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors present an adaptive multi-scale algorithm using edge and region information for segmenting intensity images into closed regions. The need for segmentation is determined by region statistics and segmentation is actually performed using edge based information. Results are shown for a number of images displaying significant improvements over mono-scale segmentation.\",\"PeriodicalId\":166931,\"journal\":{\"name\":\"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KES.1997.616854\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KES.1997.616854","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-scale adaptive segmentation using edge and region based attributes
The authors present an adaptive multi-scale algorithm using edge and region information for segmenting intensity images into closed regions. The need for segmentation is determined by region statistics and segmentation is actually performed using edge based information. Results are shown for a number of images displaying significant improvements over mono-scale segmentation.