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Clustering based Image Segmentation via Weighted Fusion of Non-local and Local Information
Guo,Li1; Chen,Long1; Philip Chen,C. L.1; Li,Tianjun1; Zhou,Jin2
2018-12-01
Source Publication2018 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2018
Pages299-303
AbstractIn this paper, we introduce a novel and effective clustering model combining the non-local and local information for the image segmentation. Recently, the non-local information has attracted much attention in the area of image processing for its excellent ability to handle the noise. Specifically, in this new model, we do an automatically weighted fusion of the non-local and local information of the image in the objective function of K-means. Thus, in the smoothing areas, the non-local information reduce the impact of noise in the region; and in the edge of regions, the local information help to keep the image details. The proposed model is a general optimization problem which can be solved by the iterative refinement technique like fuzzy c-means or K-means, and it can automatically balance the contribution of non-local and local information. Verified by the experimental results on image segmentation, the proposed model is effective to improve the performance of clustering.
Keywordautomatically balance image segmentation K-means non-local information
DOI10.1109/SPAC46244.2018.8965644
URLView the original
Language英語English
Scopus ID2-s2.0-85079148355
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Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.University of Macau,Macao
2.University of Jinan,Jinan,China
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Guo,Li,Chen,Long,Philip Chen,C. L.,et al. Clustering based Image Segmentation via Weighted Fusion of Non-local and Local Information[C], 2018, 299-303.
APA Guo,Li., Chen,Long., Philip Chen,C. L.., Li,Tianjun., & Zhou,Jin (2018). Clustering based Image Segmentation via Weighted Fusion of Non-local and Local Information. 2018 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2018, 299-303.
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