Title: Otsu multilevel thresholding segmentation based on quantum particle swarm optimisation algorithm

Authors: Lian-Lian Cao; Sheng Ding; Xiao-Wei Fu; Li Chen

Addresses: College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei, China ' College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei, China ' College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei, China ' College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei, China

Abstract: Otsu threshold segmentation is one of the most representative methods for image segmentation. Compared with multilevel threshold segmentation, Otsu method is computationally complex and time-consuming. In this paper, a multilevel thresholding algorithm based on the Quantum Particle Swarm Optimisation (QPSO) is proposed. QPSO combines the classical PSO algorithm with quantum theory. Because of the high effectiveness of QPSO optimisation algorithm, the paper combines this algorithm with Otsu and uses them in multilevel threshold image segmentation. Experiments show that the algorithm can not only realise the image multilevel threshold segmentation, but also make the segmentation more efficient.

Keywords: Otsu algorithm; multilevel threshold segmentation; QPSO; quantum PSO; particle swarm optimisation; image segmentation.

DOI: 10.1504/IJWMC.2016.077215

International Journal of Wireless and Mobile Computing, 2016 Vol.10 No.3, pp.272 - 277

Available online: 23 Jun 2016 *

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