Genetic-Greedy Hybrid Approach for Topological Active Nets Optimization

Authors:
José Santos;Óscar Ibáñez;Noelia Barreira;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;Computer Science Department, University of A Coruña, Spain
Venue:
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
Year:
2007

Citing 3
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Abstract

In this paper we propose a genetic and greedy algorithm combination for the optimization of the Topological Active Nets (TAN) model. This is a deformable model used for image segmentation that integrates features of region-based and edge-based segmentation techniques, being able to fit the edges of the objects and model their inner topology. The hybrid approach we propose can optimize the active nets through the minimization of the model energy functions and, moreover, it can provide some segmentation results unreachable by the GA method alone such as changes in the net topology.