Multilevel thresholding method for image segmentation based on an adaptive particle swarm optimization algorithm

Authors:
Chonghui Guo;Hong Li
Affiliations:
Institute of Systems Engineering, Dalian University of Technology, Dalian, P.R. China;Institute of Systems Engineering, Dalian University of Technology, Dalian, P.R. China
Venue:
AI'07 Proceedings of the 20th Australian joint conference on Advances in artificial intelligence
Year:
2007

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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.