Social spiders optimization and flower pollination algorithm for multilevel image thresholding: A performance study
作者：
Highlights：
• We present an empirical comparison of two new meta-heuristics SSO and FP.
• Real test images were used to perform thresholding using Otsu's method and Kapur's entropy.
• Compared algorithms were SSO, FP, PSO, BAT.
• Comparisons were made according to the fitness values, PSNR and SSIM.
• SSO shows superior performance in convergence and in quality terms.
摘要
•We present an empirical comparison of two new meta-heuristics SSO and FP.•Real test images were used to perform thresholding using Otsu's method and Kapur's entropy.•Compared algorithms were SSO, FP, PSO, BAT.•Comparisons were made according to the fitness values, PSNR and SSIM.•SSO shows superior performance in convergence and in quality terms.
论文关键词：Multilevel thresholding,Optimization,Social spider optimization,Flower pollination algorithm,Particle swarm optimization,Bat algorithm
论文评审过程：Received 12 July 2014, Revised 18 January 2016, Accepted 14 February 2016, Available online 3 March 2016, Version of Record 17 March 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.02.024
