Multi-level thresholding-based grey scale image segmentation using multi-objective multi-verse optimizer

作者：

Highlights：

• We propose a multi-objective version of the Multiverse Optimizer (MOMVO).

• The problem of image thresholding is solved by a multi-objective algorithm.

• The Otsu and Kapur’s methods are combined in a multi-objective problem.

• The MOMVO is tested over different images for thresholding.

• Comparisons support the performance of the proposed MOMVO.

摘要

•We propose a multi-objective version of the Multiverse Optimizer (MOMVO).•The problem of image thresholding is solved by a multi-objective algorithm.•The Otsu and Kapur’s methods are combined in a multi-objective problem.•The MOMVO is tested over different images for thresholding.•Comparisons support the performance of the proposed MOMVO.

论文关键词：Multi-verse optimizer,Multi-objective optimization,Image segmentation,Multi-level thresholding

论文评审过程：Received 15 May 2018, Revised 27 December 2018, Accepted 15 January 2019, Available online 31 January 2019, Version of Record 8 February 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.01.047