Multilevel minimum cross entropy threshold selection based on the firefly algorithm

Ming Huwi Horng, Ren Jean Liou

研究成果: Article同行評審

187 引文 斯高帕斯(Scopus)


The minimum cross entropy thresholding (MCET) has been widely applied in image thresholding. The search mechanism of firefly algorithm inspired by the social behavior of the swarms of firefly and the phenomenon of bioluminescent communication, is used to search for multilevel thresholds for image segmentation in this paper. This new multilevel thresholding algorithm is called the firefly-based minimum cross entropy thresholding (FF-based MCET) algorithm. Four different methods that are the exhaustive search, the particle swarm optimization (PSO), the quantum particle swarm optimization (QPSO) and honey bee mating optimization (HBMO) methods are implemented for comparison with the results of the proposed method. The experimental results show that the proposed FF-based MCET algorithm can efficiently search for multiple thresholds which are very close to the optimal ones examined by the exhaustive search method when the number of thresholds is less than 5. The need of computation time of using the FF-based MCET algorithm is the least, meanwhile, the results using the FF-based MCET algorithm is superior to the ones of PSO-based and QPSO-based MCET algorithms but is not significantly different to the HBMO-based MCET algorithm.

頁(從 - 到)14805-14811
期刊Expert Systems With Applications
出版狀態Published - 2011 11月

All Science Journal Classification (ASJC) codes

  • 一般工程
  • 電腦科學應用
  • 人工智慧


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