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A novel method for image segmentation based on nature inspired algorithm
Liu Y(刘洋); Hu KY(胡琨元); Zhu YL(朱云龙); Chen HN(陈瀚宁)
Department信息服务与智能控制技术研究室
Conference Name10th International Conference on Intelligent Computing, ICIC 2014
Conference DateAugust 3-6, 2014
Conference PlaceTaiyuan, China
Author of SourceIEEE Computational Intelligence Society; International Neural Network Society; National Science Foundation of China
Source PublicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Publication PlaceBerlin
2014
Pages390-402
Indexed ByEI ; CPCI(ISTP)
EI Accession number20143117998789
WOS IDWOS:000345518100046
Contribution Rank1
ISSN0302-9743
ISBN978-3-319-09329-1
KeywordAlgorithms Bioinformatics Digital Libraries Face Recognition Intelligent Computing Medical Imaging Particle Swarm Optimization (Pso)
AbstractImage segmentation is of great importance in the fields of computer vision, face recognition, medical imaging, digital libraries, and video retrieval. This paper presents a novel method for image segmentation based on a Hybrid particle swarm algorithm, which combines the advantages of swarm intelligence and the natural selection mechanism of artificial bee colony algorithm. Experimental results show that the proposed method can reach a higher quality adequate segmentation, reduce the CPU processing time and eliminate the particles falling into local minima. © 2014 Springer International Publishing Switzerland.
Language英语
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/15041
Collection信息服务与智能控制技术研究室
Affiliation1.Shenyang Institute of Automation Chinese Academy of Sciences, 110016 Shenyang, China
2.Shenyang University, 110044 Shenyang, China
3.University of Chinese Academy of Sciences, 100049 Beijing, China
Recommended Citation
GB/T 7714
Liu Y,Hu KY,Zhu YL,et al. A novel method for image segmentation based on nature inspired algorithm[C]//IEEE Computational Intelligence Society; International Neural Network Society; National Science Foundation of China. Berlin:Springer Verlag,2014:390-402.
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