Name
Title | ||
|---|---|---|
Optimization of Topological Active Models with Multiobjective Evolutionary Algorithms |
Abstract | ||
|---|---|---|
In this work we use the evolutionary multiobjective methodology for the optimization of topological active models, a deformable model that integrates features of region-based and boundary-based segmentation techniques. The model deformation is controlled by energy functions that must be minimized. As in other deformable models, a correct segmentation is achieved through the optimization of the model, governed by energy parameters that must be experimentally tuned. Evolutionary multiobjective optimization gives a solution to this problem by considering the optimization of several objectives in parallel. Concretely, we use the SPEA2 algorithm, adapted to our application, the search of the Pareto optimal individuals. The proposed method was tested on several representative images from different domains yielding highly accurate results. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICPR.2010.545 | ICPR |
Keywords | Field | DocType |
pareto optimal individual,evolutionary multiobjective optimization,multiobjective evolutionary algorithms,energy function,boundary-based segmentation technique,correct segmentation,topological active model,deformable model,energy parameter,model deformation,topological active models,evolutionary multiobjective methodology,genetic algorithm,evolutionary computation,image segmentation,genetics,gallium,optimization,genetic algorithms | Topology,Mathematical optimization,Force field (chemistry),Evolutionary algorithm,Computer science,Segmentation,Evolutionary computation,Pareto optimal,Multi-objective optimization,Image segmentation,Genetic algorithm | Conference |
Citations | PageRank | References |
1 | 0.37 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| J Novo | 1 | 89 | 18.73 |
| J. Santos | 2 | 14 | 2.49 |
| Manuel G. Penedo | 3 | 284 | 24.93 |
| A. Fernandez | 4 | 1 | 0.37 |