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https://doi.org/10.2498/cit.1001448

Fuzzy Distributed Genetic Approaches for Image Segmentation

Kamal E. Melkemi ; Department of Computer Science, University of Biskra, Algeria
Sebti Foufou ; Le2i laboratory, University of Burgundy, France and CENG, CSE, Qatar University, Qatar

Puni tekst: engleski, pdf (418 KB) str. 221-231 preuzimanja: 336* citiraj
APA 6th Edition
Melkemi, K.E. i Foufou, S. (2010). Fuzzy Distributed Genetic Approaches for Image Segmentation. Journal of computing and information technology, 18 (3), 221-231. https://doi.org/10.2498/cit.1001448
MLA 8th Edition
Melkemi, Kamal E. i Sebti Foufou. "Fuzzy Distributed Genetic Approaches for Image Segmentation." Journal of computing and information technology, vol. 18, br. 3, 2010, str. 221-231. https://doi.org/10.2498/cit.1001448. Citirano 25.06.2019.
Chicago 17th Edition
Melkemi, Kamal E. i Sebti Foufou. "Fuzzy Distributed Genetic Approaches for Image Segmentation." Journal of computing and information technology 18, br. 3 (2010): 221-231. https://doi.org/10.2498/cit.1001448
Harvard
Melkemi, K.E., i Foufou, S. (2010). 'Fuzzy Distributed Genetic Approaches for Image Segmentation', Journal of computing and information technology, 18(3), str. 221-231. doi: https://doi.org/10.2498/cit.1001448
Vancouver
Melkemi KE, Foufou S. Fuzzy Distributed Genetic Approaches for Image Segmentation. Journal of computing and information technology [Internet]. 2010 [pristupljeno 25.06.2019.];18(3):221-231. doi: https://doi.org/10.2498/cit.1001448
IEEE
K.E. Melkemi i S. Foufou, "Fuzzy Distributed Genetic Approaches for Image Segmentation", Journal of computing and information technology, vol.18, br. 3, str. 221-231, 2010. [Online]. doi: https://doi.org/10.2498/cit.1001448

Sažetak
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.

Hrčak ID: 59536

URI
https://hrcak.srce.hr/59536

Posjeta: 474 *