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A multi-level thresholding image segmentation based on an improved artificial bee colony algorithm
Gao, Hao1,2; Fu, Zheng1; Pun, Chi-Man2; Hu, Haidong3; Lan, Rushi4,5
2018-08
Source PublicationCOMPUTERS & ELECTRICAL ENGINEERING
ISSN0045-7906
Volume70Pages:931-938
Abstract

As a popular evolutionary algorithm, Artificial Bee Colony (ABC) algorithm has been successfully applied into threshold-based image segmentation. Due to its one dimension search strategy, the convergence speed of ABC is slow and its solution is acceptable but not precise. For making more fine-tuning search and further enhancing the achievements on image segmentation, we proposed an Otsu segmentation method based on a new ABC algorithm. Different from the traditional ABC strategy, our algorithm takes full use of individuals information which is defined by a focus point and the best point to increase its accuracy and convergence speed. Furtheremore, we propose an adaptive parameter to adjust the search step of individual automatically, which also improves its exploitation ability. Experimental results on Berkeley segmentation database demonstrate the effectiveness of our algorithm. (C) 2017 Elsevier Ltd. All rights reserved.

KeywordImage Segmentation Otsu Artificial Bee Colony Convergence Speed Precise Search
DOI10.1016/j.compeleceng.2017.12.037
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Hardware & Architecture ; Computer Science, Interdisciplinary Applications ; Engineering, Electrical & Electronic
WOS IDWOS:000446151100066
PublisherPERGAMON-ELSEVIER SCIENCE LTD
The Source to ArticleWOS
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Citation statistics
Cited Times [WOS]:11   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorGao, Hao
Affiliation1.The Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing, China
2.Department of Computer and Information Science, University of Macau, Macau SAR, China
3.Beijing Institute of Control Engineering, Beijing, China
4.School of Computer Science & Engineering, South China University of Technology, China
5.School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, China
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Gao, Hao,Fu, Zheng,Pun, Chi-Man,et al. A multi-level thresholding image segmentation based on an improved artificial bee colony algorithm[J]. COMPUTERS & ELECTRICAL ENGINEERING,2018,70:931-938.
APA Gao, Hao,Fu, Zheng,Pun, Chi-Man,Hu, Haidong,&Lan, Rushi.(2018).A multi-level thresholding image segmentation based on an improved artificial bee colony algorithm.COMPUTERS & ELECTRICAL ENGINEERING,70,931-938.
MLA Gao, Hao,et al."A multi-level thresholding image segmentation based on an improved artificial bee colony algorithm".COMPUTERS & ELECTRICAL ENGINEERING 70(2018):931-938.
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