| Research Title |
Multilevel thresholding selection based on chaotic multi-verse optimization for image segmentation |
| Date of Distribution |
21 November 2016 |
| Conference |
| Title of the Conference |
13th International Joint Conference on Computer Science and Software Engineering (JCSSE), 2016 |
| Organiser |
Department of computer Science, Faculty of Science, Khon Kaen University, Thailand |
| Conference Place |
Pullman Khon Kaen Raja Orchid Hotel, Khon Kaen, Thailand |
| Province/State |
Khon Kaen |
| Conference Date |
13 July 2016 |
| To |
15 July 2016 |
| Proceeding Paper |
| Volume |
2016 |
| Issue |
5 |
| Page |
1 - 6 |
| Editors/edition/publisher |
|
| Abstract |
Multilevel thresholding is the most important method for image processing. Conventional multilevel thresholding methods have proven to be efficient in bi-level thresholding; however, when extended to multilevel thresholding, they prove to be computationally more costly, as they comprehensively search the optimal thresholds for the objective function. This paper presents a chaotic multi-verse optimizer (CMVO) algorithm using Kapur's objective function in order to determine the optimal multilevel thresholds for image segmentation. The proposed CMVO algorithm was applied to various standard test images, and evaluated by peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). The CMVO algorithm efficiently and accurately searched multilevel thresholds and reduced the required computational times. |
| Author |
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| Peer Review Status |
มีผู้ประเมินอิสระ |
| Level of Conference |
นานาชาติ |
| Type of Proceeding |
Full paper |
| Type of Presentation |
Oral |
| Part of thesis |
true |
| Presentation awarding |
false |
| Attach file |
|
| Citation |
0
|
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Publication
Journal Publication
ไทย