Original scientific paper
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
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.
Keywords
Hrčak ID:
59536
URI
Publication date:
30.9.2010.
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