Abstract
The Topological Active Net (TAN) model is a deformable model used for image segmentation. It integrates features of region–based and edge–based segmentation techniques. This way, the model is able to fit the edges of the objects and model their inner topology. The model consists of a two dimensional mesh controlled by energy functions. The minimization of these energy functions leads to the TAN adjustment.
This paper presents a new approach to the energy minimization process based on genetic algorithms (GA), that defines several suitable genetic operators for the optimization task. The results of the new GA approach are compared to the results of a greedy algorithm developed for the same task.
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© 2006 Springer-Verlag Berlin Heidelberg
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Ibáñez, O., Barreira, N., Santos, J., Penedo, M.G. (2006). Topological Active Nets Optimization Using Genetic Algorithms. In: Campilho, A., Kamel, M.S. (eds) Image Analysis and Recognition. ICIAR 2006. Lecture Notes in Computer Science, vol 4141. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11867586_26
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DOI: https://doi.org/10.1007/11867586_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44891-4
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