Abstract
The multilevel thresholding method with maximum entropy is one of the most important image segmentation methods in image processing. However, its time-consuming computation is often an obstacle in real time application systems. Particle swarm optimization (PSO) algorithm is a class of heuristic global optimization algorithms which appeared recently. In this paper, the maximum entropy is obtained through an adaptive particle swarm optimization (APSO) algorithm. The APSO algorithm is shown to obtain the maximum entropy of multilevel thresholding effectively on experiments of image segmentation. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Guo, C., & Li, H. (2007). Multilevel thresholding method for image segmentation based on an adaptive particle swarm optimization algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4830 LNAI, pp. 654–658). Springer Verlag. https://doi.org/10.1007/978-3-540-76928-6_70
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