Abstract
Active contours, very popular in image segmentation, suffer from delicate adjustments of many parameters. We propose to carry out these adjustments using genetic algorithm. Here an active contour is implemented using a greedy algorithm. Within this framework, two approaches are presented. A supervised approach which delivers a global set of parameters. In this case the greedy algorithm is involved in the evaluation function of the genetic algorithm. The second approach is unsupervised. It determines a local set of parameters. The genetic algorithm computes a set of parameters which minimizes the energy at each point in the neighborhood of the current point in the greedy algorithm try to move.
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© 2003 Springer-Verlag Berlin Heidelberg
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Rousselle, JJ., Vincent, N., Verbeke, N. (2003). Genetic Algorithm to Set Active Contour. In: Petkov, N., Westenberg, M.A. (eds) Computer Analysis of Images and Patterns. CAIP 2003. Lecture Notes in Computer Science, vol 2756. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45179-2_43
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DOI: https://doi.org/10.1007/978-3-540-45179-2_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40730-0
Online ISBN: 978-3-540-45179-2
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