Evolutionary Game Algorithm for Image Segmentation
Joint Authors
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-07-25
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
The traditional two-dimensional Otsu algorithm only considers the limitations of the maximum variance of between-cluster variance of the target class and background class; this paper proposes evolutionary game improved algorithm.
Algorithm takes full consideration of own pixel cohesion of target and background.
It can meet the same of maximum variance of between-cluster variance.
To ensure minimum threshold discriminant function within the variance, this kind of evolutionary game algorithm searching space for optimal solution is applied.
Experimental results show that the method proposed in this paper makes the detail of segmentation image syllabify and has better antijamming capability; the improved genetic algorithm which used searching optimal solution has faster convergence speed and better global search capability.
American Psychological Association (APA)
Zhong, Jin& Wu, Hao. 2017. Evolutionary Game Algorithm for Image Segmentation. Journal of Electrical and Computer Engineering،Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1175434
Modern Language Association (MLA)
Zhong, Jin& Wu, Hao. Evolutionary Game Algorithm for Image Segmentation. Journal of Electrical and Computer Engineering No. 2017 (2017), pp.1-10.
https://search.emarefa.net/detail/BIM-1175434
American Medical Association (AMA)
Zhong, Jin& Wu, Hao. Evolutionary Game Algorithm for Image Segmentation. Journal of Electrical and Computer Engineering. 2017. Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1175434
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175434