Computer Science ›› 2014, Vol. 41 ›› Issue (8): 289-292.doi: 10.11896/j.issn.1002-137X.2014.08.061

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Gaussian Mixture Model Terrain Classification Based on Hybrid PSO

HAN Guang,SUN Ning,LI Xiao-fei and ZHAO Chun-xia   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Gaussian mixture model terrain classification based on improved hybrid particle swarm optimization (PSO) algorithm was presented.The expectation-maximization (EM) method is a popular method to solve the Gaussian mixture model,but it is a local optimization method with instable convergence rate and initial value sensitivity.Therefore the hybrid PSO algorithm was introduced,and a series of improvement was conducted.Experimental results show that the improved algorithm can greatly improve the global convergence ability and enhance the rate of convergence.Using the improved algorithm to solve Gaussian mixture model can improve the accuracy of parameter estimation,and the proposed terrain classification method also has excellent performance in the terrain classification experiment of outdoor scene image.

Key words: Hybrid pso algorithm,Gaussian mixture model,EM algorithm,Terrain classification

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