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Bayesian learning, global competition and unsupervised image segmentation
Guo, GD; Ma, SD
2000-02-01
发表期刊PATTERN RECOGNITION LETTERS
卷号21期号:2页码:107-116
文章类型Article
摘要A novel approach to unsupervised stochastic model-based image segmentation is presented and the problems of parameter estimation and image segmentation are formulated as Bayesian learning. In order to draw samples corresponding to different classes, a global competition strategy is adopted for label commitment based on the "powervalue" (PV) associated with each sample (or site). The smaller the value, the more powerful the sample to compete. Parameter estimation and image segmentation are executed in the same process. Bayesian modeling of images by Markov random fields (MRFs) makes it easy to represent the power of each site for competition. The new procedure to unsupervised image segmentation is performed on synthetic and real images to show its success. (C) 2000 Elsevier Science B.V. All rights reserved.
关键词Bayesian Learning Global Competition Unsupervised Image Segmentation Markov Random Field Parameter Estimation
WOS标题词Science & Technology ; Technology
收录类别SCI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000085423600002
引用统计
被引频次:4[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/9791
专题09年以前成果
作者单位1.Nanyang Technol Univ, Sch Elect & Elect Engn, Intelligent Machine Res Lab, Singapore 639798, Singapore
2.CAS, NLPR, Inst Automat, Beijing 100080, Peoples R China
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Guo, GD,Ma, SD. Bayesian learning, global competition and unsupervised image segmentation[J]. PATTERN RECOGNITION LETTERS,2000,21(2):107-116.
APA Guo, GD,&Ma, SD.(2000).Bayesian learning, global competition and unsupervised image segmentation.PATTERN RECOGNITION LETTERS,21(2),107-116.
MLA Guo, GD,et al."Bayesian learning, global competition and unsupervised image segmentation".PATTERN RECOGNITION LETTERS 21.2(2000):107-116.
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