{"title":"图像区域分割的层次聚类模型","authors":"J. Randall, L. Guan, Xing Zhang, W. Li","doi":"10.1109/ICME.2002.1035876","DOIUrl":null,"url":null,"abstract":"The hierarchical cluster model (HCM), a neural network inspired by the human brain (see Sutton, J., Harvard Medical School, MIT, Neural Systems Group, Technical Report, 1995), is demonstrated for the purpose of region segmentation in digital images. Starting with an over segmented image, regions are merged based on evidence of a valid edge between the two regions. Unlike Sutton's work, in which the HCM is used to recall a set of pre-trained memory patterns, the HCM in our work demonstrates unsupervised decision making capabilities.","PeriodicalId":90694,"journal":{"name":"Proceedings. IEEE International Conference on Multimedia and Expo","volume":"93 1","pages":"693-696 vol.1"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"The hierarchical cluster model for image region segmentation\",\"authors\":\"J. Randall, L. Guan, Xing Zhang, W. Li\",\"doi\":\"10.1109/ICME.2002.1035876\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The hierarchical cluster model (HCM), a neural network inspired by the human brain (see Sutton, J., Harvard Medical School, MIT, Neural Systems Group, Technical Report, 1995), is demonstrated for the purpose of region segmentation in digital images. Starting with an over segmented image, regions are merged based on evidence of a valid edge between the two regions. Unlike Sutton's work, in which the HCM is used to recall a set of pre-trained memory patterns, the HCM in our work demonstrates unsupervised decision making capabilities.\",\"PeriodicalId\":90694,\"journal\":{\"name\":\"Proceedings. IEEE International Conference on Multimedia and Expo\",\"volume\":\"93 1\",\"pages\":\"693-696 vol.1\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. IEEE International Conference on Multimedia and Expo\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICME.2002.1035876\",\"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. IEEE International Conference on Multimedia and Expo","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICME.2002.1035876","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
摘要
层次聚类模型(HCM)是一种受人脑启发的神经网络(见Sutton, J.， Harvard Medical School, MIT, neural Systems Group, Technical Report, 1995)，用于数字图像的区域分割。从过度分割的图像开始，基于两个区域之间有效边缘的证据合并区域。与萨顿的研究不同，在萨顿的研究中，HCM被用来回忆一组预先训练的记忆模式，而我们的研究中，HCM展示了无监督的决策能力。
The hierarchical cluster model for image region segmentation
The hierarchical cluster model (HCM), a neural network inspired by the human brain (see Sutton, J., Harvard Medical School, MIT, Neural Systems Group, Technical Report, 1995), is demonstrated for the purpose of region segmentation in digital images. Starting with an over segmented image, regions are merged based on evidence of a valid edge between the two regions. Unlike Sutton's work, in which the HCM is used to recall a set of pre-trained memory patterns, the HCM in our work demonstrates unsupervised decision making capabilities.
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