Multilevel Image Thresholding Selection Based on the Cuckoo Search Algorithm
نویسندگان
چکیده
The drawback of the conventional multilevel thresholding methods is high computational cost since they do exhaustive search among exponentialy growing number of possible thresholds to optimize the objective functions. In this paper a new multilevel thresholding method based on cuckoo search (CS) algorithm is proposed in order to overcome this obstacle. The optimal thresholds are found by maximizing Kapur's thresholding function. Particle swarm optimization (PSO) algorithm is also implemented and compared to our proposed method. Both algorithms have been tested on four sample images and the experimental results obtained by our proposed CS based method have been found to be better than those obtained by PSO algorithm. Key-Words: Maximum entropy thresholding, Image thresholding, Cuckoo search algorithm, Particle swarm optimization, Nature inspired metaheuristics, Swarm intelligence
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