| Título: | MRF-based image segmentation using Ant Colony System |
| Autores: |
Ouadfel, Salima Batouche, Mohamed |
| Fecha: | 1970-01-01 |
| Publicador: | CVC Press |
| Fuente: |
Ver documento |
| Tipo: | |
| Tema: | clustering; image segmentation and image extraction; Markov Random Field; Optimization; Ant Colony System |
| Descripción: | In this paper, we propose a novel method for image segmentation that we call ACS-MRF method. ACS-MRF is a hybrid ant colony system coupled with a local search. We show how a colony of cooperating ants are able to estimate the labels field and minimize the MAP estimate. Cooperation between ants is performed by exchanging information through pheromone updating. The obtained results show the efficiency of the new algorithm, which is able to compete with other stochastic optimization methods like Simulated annealing and Genetic algorithm in terms of solution quality. keywords: clustering, image segmentation and image extraction, Markov Random Field, Optimization, Ant Colony System |
| Idioma: | No aplica |