Modified salp swarm algorithm based multilevel thresholding for color image segmentation

• Main Authors: Shikai Wang, Heming Jia, Xiaoxu Peng
• Format: Article
• Language: English
• Published: AIMS Press 2020-01-01
• Series: Mathematical Biosciences and Engineering
• Subjects: multi-threshold color image segmentation; kapur's entropy method; slap swarm optimization; levy flight
• Online Access: https://www.aimspress.com/article/doi/10.3934/mbe.2020036?viewType=HTML

This paper proposes a multi-threshold image segmentation method based on modified salp swarm algorithm (SSA). Multi-threshold image segmentation method has good segmentation effect, but the segmentation precision will be affected with the increase of threshold number. To avoid the above problem, the slap swarm optimization algorithm (SSA) is presented to choose the optimal parameters of the fitting function and we use levy flight to improve the SSA. The solutions are assessed using the Kapur's entropy, Otsu and Renyi entropy fitness function during the optimization operation. The performance of the proposed algorithm is evaluated with several reference images and compared with different group algorithms. The results have been analyzed based on the best fitness values, peak signal to noise ratio (PSNR), and feature similarity index measures (FSIM). The experimental results show that the proposed algorithm outperformed other swarm algorithms.