Color image segmentation using Kapur, Otsu and Minimum Cross Entropy functions based on Exchange Market Algorithm

作者：

Highlights：

• A color image segmentation based on Exchange Market Algorithm (EMA) is proposed.

• Between class variance and entropy functions are used as objective functions.

• The proposed EMA approach is compared with other state-of-the-art algorithms.

• Results reveal that the EMA is the effective approach for multilevel thresholding.

摘要

•A color image segmentation based on Exchange Market Algorithm (EMA) is proposed.•Between class variance and entropy functions are used as objective functions.•The proposed EMA approach is compared with other state-of-the-art algorithms.•Results reveal that the EMA is the effective approach for multilevel thresholding.

论文关键词：Exchange Market Algorithm,Image segmentation,Krill Herd Algorithm,Minimum Cross Entropy,Multilevel thresholding

论文评审过程：Received 12 March 2020, Revised 18 January 2021, Accepted 18 January 2021, Available online 26 January 2021, Version of Record 13 February 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.114636