Computer Science ›› 2017, Vol. 44 ›› Issue (6): 278-282.doi: 10.11896/j.issn.1002-137X.2017.06.049

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Fuzzy Clustering Image Segmentation Algorithm Based on Improved Cuckoo Search

ZHU Chun, LI Lin-guo and GUO Jian   

  • Online:2018-11-13 Published:2018-11-13

Abstract: Fuzzy C-means clustering algorithm(FCM) is a widely used clustering algorithm,however,it is influenced by the initial cluster centers,and is easy to fall into local optima.In this article,we proposed an improved cuckoo search(ICS) based on the standard cuckoo algorithm(CS),which changes the detection probability P with a constant value into a variable number of iterations decreases.This will not only improve the quality of the population,but also ensure the convergence of the algorithm.Therefore,we can use the improved cuckoo search algorithm to generate the FCM clustering centers and avoid FCM falling into local optima effectively.The proposed algorithm has better clustering effect and faster running speed.In this article,ICS_FCM was used in fuzzy clustering image segmentation,and compared with SA_FCM.The experimental results show that ICS_FCM can not only achieve better segmentation results,but also improved efficiency significantly.

Key words: Image segmentation,Improved cuckoo search algorithm,Fuzzy C-means clustering

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