Many-objectives multilevel thresholding image segmentation using Knee Evolutionary Algorithm

作者：

Highlights：

• Formulate the Multi-level threshold image segmentation as a MaOPs.

• Using the KnEA algorithm to find the threshold values for the given image.

• Using seven functions to evaluate the quality of each solution.

• Compare the proposed KnEA method with other four MaOP algorithms.

• The performance of KnEA is better than other MaOPs in locating threshold values.

摘要

•Formulate the Multi-level threshold image segmentation as a MaOPs.•Using the KnEA algorithm to find the threshold values for the given image.•Using seven functions to evaluate the quality of each solution.•Compare the proposed KnEA method with other four MaOP algorithms.•The performance of KnEA is better than other MaOPs in locating threshold values.

论文关键词：Metaheuristic method (MH),Swarm Selection,Image segmentation,Multilevel thresholding

论文评审过程：Received 25 November 2018, Revised 8 January 2019, Accepted 29 January 2019, Available online 6 February 2019, Version of Record 12 February 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.01.075