{"title":"一种新的基于som的主动轮廓建模方法","authors":"Y. Venkatesh, S. Raja, N. Ramya","doi":"10.1109/ISSNIP.2004.1417467","DOIUrl":null,"url":null,"abstract":"We integrate the advantages of SOM- and snake-based ACMs in order to extract the desired contour from images. We employ: (i) the feature points to guide the contour, as in the case of SOM-based ACMs; (ii) the gradient and intensity variations in a local region to control the contour movement. However, in contrast with the snake-based ACMs, we do not use an explicit energy functional based on gradient or intensity. The algorithm is tested on synthetic binary and gray-level images, and the results show the superiority of the proposed algorithm over other conventional SOM- and snake-based ACM algorithms.","PeriodicalId":147043,"journal":{"name":"Proceedings of the 2004 Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"A novel SOM-based approach for active contour modeling\",\"authors\":\"Y. Venkatesh, S. Raja, N. Ramya\",\"doi\":\"10.1109/ISSNIP.2004.1417467\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We integrate the advantages of SOM- and snake-based ACMs in order to extract the desired contour from images. We employ: (i) the feature points to guide the contour, as in the case of SOM-based ACMs; (ii) the gradient and intensity variations in a local region to control the contour movement. However, in contrast with the snake-based ACMs, we do not use an explicit energy functional based on gradient or intensity. The algorithm is tested on synthetic binary and gray-level images, and the results show the superiority of the proposed algorithm over other conventional SOM- and snake-based ACM algorithms.\",\"PeriodicalId\":147043,\"journal\":{\"name\":\"Proceedings of the 2004 Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004.\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2004 Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSNIP.2004.1417467\",\"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 the 2004 Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSNIP.2004.1417467","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel SOM-based approach for active contour modeling
We integrate the advantages of SOM- and snake-based ACMs in order to extract the desired contour from images. We employ: (i) the feature points to guide the contour, as in the case of SOM-based ACMs; (ii) the gradient and intensity variations in a local region to control the contour movement. However, in contrast with the snake-based ACMs, we do not use an explicit energy functional based on gradient or intensity. The algorithm is tested on synthetic binary and gray-level images, and the results show the superiority of the proposed algorithm over other conventional SOM- and snake-based ACM algorithms.