Abstract
In this paper, we present an application of three heuristic optimization algorithms to computing tree-based image dissimilarity. Genetic algorithm, particle swarm optimization and simulated annealing have been applied to optimize a blackbox function which aims to determine a difference between two trees, constructed upon binary images. Presented results show that the particle swarm optimization achieved the best results. Both PSO and the simulated annealing outperformed the genetic algorithm. We also draw conclusions on parameter adjustment for the considered methods.
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Zieliński, B., Iwanowski, M. (2013). Heuristic Optimization Algorithms for a Tree-Based Image Dissimilarity Measure. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds) Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Advances in Intelligent Systems and Computing, vol 226. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00969-8_9
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DOI: https://doi.org/10.1007/978-3-319-00969-8_9
Publisher Name: Springer, Heidelberg
Print ISBN: 978-3-319-00968-1
Online ISBN: 978-3-319-00969-8
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