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Improved mean shift segmentation approach for natural images
Hong, Yiping; Yi, Jianqiang; Zhao, Dongbin
Source PublicationAPPLIED MATHEMATICS AND COMPUTATION
2007-02-15
Volume185Issue:2Pages:940-952
SubtypeArticle
AbstractThis paper proposes an improved natural image segmentation approach that is more effective, more controllable and more stable under various backgrounds than the traditional mean shift segmentation. The proposed approach employs following four new aspects: the changeable color bandwidth, the direct density searching, the global optimization for mode merging, and the elimination of texture patches. In bandwidth selection, the optimal color bandwidth under Plug-in rule used by the traditional approach is not suitable for actual vision tasks, and a changeable color bandwidth makes it easy to control the segmentation result. The performance of the direct density searching is better than that of mean shift under the same spatial bandwidth. A global optimization criterion for mode merging stabilizes the segmentation result of different images. The elimination of texture patches mostly removes the small patches resulting from texture. In addition, after mode detection, an image is partitioned into some local patches, each of which corresponds to a local mode. These patches are got with color information, and they can be taken as the initial segmentation for further processing that is based on a global optimization criterion constructed by texture features. (c) 2006 Elsevier Inc. All rights reserved.
KeywordNatural Image Segmentation Mean Shift Mode Detection Density Estimation
WOS HeadingsScience & Technology ; Physical Sciences
WOS KeywordACTIVE CONTOURS ; REGION COMPETITION ; COLOR ; GRADIENT
Indexed BySCI ; ISTP
Language英语
WOS Research AreaMathematics
WOS SubjectMathematics, Applied
WOS IDWOS:000245762700017
Citation statistics
Cited Times:10[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9432
Collection09年以前成果
Corresponding AuthorHong, Yiping
AffiliationChinese Acad Sci, Inst Automat, Lab Complex Syst & Intelligence Sci, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Hong, Yiping,Yi, Jianqiang,Zhao, Dongbin. Improved mean shift segmentation approach for natural images[J]. APPLIED MATHEMATICS AND COMPUTATION,2007,185(2):940-952.
APA Hong, Yiping,Yi, Jianqiang,&Zhao, Dongbin.(2007).Improved mean shift segmentation approach for natural images.APPLIED MATHEMATICS AND COMPUTATION,185(2),940-952.
MLA Hong, Yiping,et al."Improved mean shift segmentation approach for natural images".APPLIED MATHEMATICS AND COMPUTATION 185.2(2007):940-952.
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