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http://archives.univ-biskra.dz/handle/123456789/2351| Title: | Fuzzy Distributed Genetic Approaches for Image Segmentation |
| Authors: | Kamal E. Melkemi Sebti Foufou |
| Keywords: | image segmentation, fuzzy logic, Markov, random field, multiagent systems, genetic algorithms, chaotic system. |
| Issue Date: | 18-Apr-2014 |
| Abstract: | This paper presents a new image segmentation algorithm (called FDGA-Seg) based on a combination of fuzzy logic, multiagent systems and genetic algorithms. We propose to use a fuzzy representation of the image site labels by introducing some imprecision in the gray tones values. The distributivity of FDGA-Seg comes from the fact that it is designed around a MultiAgent System (MAS) working with two different architectures based on the master-slave and island models. A rich set of experimental segmentation results given by FDGA-Seg is discussed and compared to the ICM results in the last section. DOI: 10.2498/cit.1001889 Link http://cit.srce.unizg.hr/index.php/CIT/article/view/1889 |
| URI: | http://archives.univ-biskra.dz/handle/123456789/2351 |
| Appears in Collections: | Publications Internationales |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Fuzzy Distributed Genetic Approaches for Image Segmentation.pdf | 35,7 kB | Adobe PDF | View/Open |
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