Name
Abstract | ||
|---|---|---|
In this work it is proposed an evolutionary multiobjective methodology for the optimization of topological active volumes. This is a 3D 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. Most optimization algorithms need an experimental tuning of the energy parameters of the model in order to obtain the best adjusted segmentation.To avoid the step of the parameter tuning, we developed an evolutionary multiobjective optimization that considers the optimization of several objectives in parallel. The proposed methodology is based on the SPEA2 algorithm, adapted to our application, to obtain the Pareto optimal individuals. The proposed method was tested on several representative images from different domains yielding highly accurate results. |
Year | Venue | Keywords |
|---|---|---|
2011 | ICAART 2011: PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE, VOL 1 | Deformable segmentation models, Genetic algorithms, Evolutionary multiobjective optimization |
Field | DocType | Citations |
Data mining,Computer science,Segmentation,Multi-objective optimization | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jorge Novo | 1 | 25 | 6.18 |
| Manuel G. Penedo | 2 | 185 | 35.91 |
| José Santos Reyes | 3 | 75 | 16.25 |