Computer Science ›› 2016, Vol. 43 ›› Issue (3): 309-312.doi: 10.11896/j.issn.1002-137X.2016.03.058

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Otsu Image Threshold Segmentation Method Based on Improved Particle Swarm Optimization

LIU Gui-hong, ZHAO Liang, SUN Jin-guang and WANG Xing   

  • Online:2018-12-01 Published:2018-12-01

Abstract: The thresholding method only needs the gray information to spilt image,which is more intuitive and much easier to be implemented.Aiming at the problem that the traditional PSO algorithm used for image segmentation is easy to fall into local optimum,this paper proposed an Otsu image threshold segmentation method based on the improved PSO.We took the inter-class variance of Otsu as the fitness function,and selected the particles with better fitness and added new particles to increase the diversity of the particles.The experimental results show that,compared with Otsu methods and PSO algorithm,the improved PSO accelerates the speed of convergence and computation,and improves the accuracy of image segmentation.

Key words: Image segmentation,Otsu,Inter-class variance,Particle swarm optimization,Fitness function

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