Optimization of topological active nets with differential evolution

Authors:
Jorge Novo;José Santos;Manuel G. Penedo
Affiliations:
Computer Science Department, University of A Coruña, Spain;Computer Science Department, University of A Coruña, Spain;Computer Science Department, University of A Coruña, Spain
Venue:
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part I
Year:
2011

Citing 5
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Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: In Search of Solutions (Springer Optimization and Its Applications)

Differential Evolution: In Search of Solutions (Springer Optimization and Its Applications)
Genetic approaches for topological active nets optimization

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Particle Swarm Optimization and Differential Evolution for model-based object detection

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Multiobjective differential evolution in the optimization of topological active models

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Abstract

The Topological ActiveNetmodel for image segmentation is a deformable model that integrates features of region-based and boundary-based segmentation techniques. The segmentation process turns into a minimization task of the energy functions which control the model deformation. We used Differential Evolution as an alternative evolutionary method that minimizes the decisions of the designer with respect to other evolutionary methods such as genetic algorithms.Moreover, we hybridized Differential Evolution with a greedy search to integrate the advantages of global and local searches at the same time that the segmentation speed is improved.