Improved Particle Swarm Optimization Algorithm for Image Segmentation

doi:10.23940/ijpe.20.03.p18.482489

Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (3): 482-489.doi: 10.23940/ijpe.20.03.p18.482489

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Improved Particle Swarm Optimization Algorithm for Image Segmentation

Youfen Chen

School of Intelligent Manufacturing, Shunde Polytechnic, Foshan, Guangdong, 528333, China

Submitted on ; Revised on ; Accepted on
Contact: Youfen Chen E-mail:gdsdcyf@126.com
About author:Youfen Chen is currently a lecturer in the Shunde Polytechnic. She received her Master of engineering degree of Application of computer from Hubei University.Her research interests is Image algorithm.

Abstract

Abstract: Aiming at the shortcomings of longtime consumption and complex algorithm in multi-threshold image segmentation, the maximum inter-class variance method and the maximum entropy threshold method are described as segmentation standards. Secondly, from the point of view of initialization and falling into local optimization of particle swarm optimization algorithm, Kent mapping is introduced, and nonlinear digressive extremum is improved. Finally, the improved particle swarm optimization algorithm is applied to multi-threshold image segmentation. Simulation results show that the algorithm has a good segmentation effect and the time consumption can be effectively reduced.

Key words: image segmentation, particle swarm optimization algorithm, multi-threshold

Youfen Chen. Improved Particle Swarm Optimization Algorithm for Image Segmentation [J]. Int J Performability Eng, 2020, 16(3): 482-489.

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Improved Particle Swarm Optimization Algorithm for Image Segmentation

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