Abstract
In this paper, we propose a new Chaotic MultiAgent System (CMAS) for image segmentation. This CMAS is a distributed system composed of a set of segmentation agents connected to a coordinator agent. Each segmentation agent performs Iterated Conditional Modes (ICM) starting from its own initial image created initially from the observed one by using a chaotic mapping. However, the coordinator agent receives and diversifies these images using a crossover and a chaotic mutation. A chaotic system is successfully used in order to benefit from the special chaotic characteristic features such as ergodic property, stochastic aspect and dependence on initialization. The efficiency of our approach is shown through experimental results.
| Original language | English (US) |
|---|---|
| Title of host publication | Fuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers |
| Pages | 344-353 |
| Number of pages | 10 |
| DOIs | |
| State | Published - Jun 23 2006 |
| Event | 6th International Workshop - Fuzzy Logic and Applications - Crema, Italy Duration: Sep 15 2005 → Sep 17 2005 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 3849 LNAI |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 6th International Workshop - Fuzzy Logic and Applications |
|---|---|
| Country | Italy |
| City | Crema |
| Period | 9/15/05 → 9/17/05 |
Fingerprint
Keywords
- Chaotic System
- Genetic Algorithms
- Image Segmentation
- Markov Random Field
- MultiAgent Systems
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
Cite this
MRF model-based approach for image segmentation using a chaotic MultiAgent system. / Melkemi, Kamal E.; Batouche, Mohamed; Foufou, Sebti.
Fuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers. 2006. p. 344-353 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3849 LNAI).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - MRF model-based approach for image segmentation using a chaotic MultiAgent system
AU - Melkemi, Kamal E.
AU - Batouche, Mohamed
AU - Foufou, Sebti
PY - 2006/6/23
Y1 - 2006/6/23
N2 - In this paper, we propose a new Chaotic MultiAgent System (CMAS) for image segmentation. This CMAS is a distributed system composed of a set of segmentation agents connected to a coordinator agent. Each segmentation agent performs Iterated Conditional Modes (ICM) starting from its own initial image created initially from the observed one by using a chaotic mapping. However, the coordinator agent receives and diversifies these images using a crossover and a chaotic mutation. A chaotic system is successfully used in order to benefit from the special chaotic characteristic features such as ergodic property, stochastic aspect and dependence on initialization. The efficiency of our approach is shown through experimental results.
AB - In this paper, we propose a new Chaotic MultiAgent System (CMAS) for image segmentation. This CMAS is a distributed system composed of a set of segmentation agents connected to a coordinator agent. Each segmentation agent performs Iterated Conditional Modes (ICM) starting from its own initial image created initially from the observed one by using a chaotic mapping. However, the coordinator agent receives and diversifies these images using a crossover and a chaotic mutation. A chaotic system is successfully used in order to benefit from the special chaotic characteristic features such as ergodic property, stochastic aspect and dependence on initialization. The efficiency of our approach is shown through experimental results.
KW - Chaotic System
KW - Genetic Algorithms
KW - Image Segmentation
KW - Markov Random Field
KW - MultiAgent Systems
UR - http://www.scopus.com/inward/record.url?scp=33745126248&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33745126248&partnerID=8YFLogxK
U2 - 10.1007/11676935_43
DO - 10.1007/11676935_43
M3 - Conference contribution
SN - 3540325298
SN - 9783540325291
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 344
EP - 353
BT - Fuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers
ER -