Evolutionary Game Algorithm for Image Segmentation
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...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2017/8746010 |
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| _version_ | 1832568459790123008 |
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| author | Jin Zhong Hao Wu |
| author_facet | Jin Zhong Hao Wu |
| author_sort | Jin Zhong |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-cfff4ef8c6e2443780fd8781191ff0a2 |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-cfff4ef8c6e2443780fd8781191ff0a22025-02-03T00:59:01ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552017-01-01201710.1155/2017/87460108746010Evolutionary Game Algorithm for Image SegmentationJin Zhong0Hao Wu1College of Computer Science, Hefei Normal University, Hefei 230601, ChinaCollege of Computer Science, Hefei Normal University, Hefei 230601, ChinaThe 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.http://dx.doi.org/10.1155/2017/8746010 |
| spellingShingle | Jin Zhong Hao Wu Evolutionary Game Algorithm for Image Segmentation Journal of Electrical and Computer Engineering |
| title | Evolutionary Game Algorithm for Image Segmentation |
| title_full | Evolutionary Game Algorithm for Image Segmentation |
| title_fullStr | Evolutionary Game Algorithm for Image Segmentation |
| title_full_unstemmed | Evolutionary Game Algorithm for Image Segmentation |
| title_short | Evolutionary Game Algorithm for Image Segmentation |
| title_sort | evolutionary game algorithm for image segmentation |
| url | http://dx.doi.org/10.1155/2017/8746010 |
| work_keys_str_mv | AT jinzhong evolutionarygamealgorithmforimagesegmentation AT haowu evolutionarygamealgorithmforimagesegmentation |