Optimization of Topological Active Models with Multiobjective Evolutionary Algorithms

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.