Opposition-based Laplacian Equilibrium Optimizer with application in Image Segmentation using Multilevel Thresholding

作者：

Highlights：

• Proposed novel Opposition-based Laplacian Equilibrium Optimizer.

• Applied techniques improve macro and micro search abilities.

• Performance is verified over a set of 23 benchmark problems.

• Applied in image segmentation using Multi-level thresholding.

摘要

•Proposed novel Opposition-based Laplacian Equilibrium Optimizer.•Applied techniques improve macro and micro search abilities.•Performance is verified over a set of 23 benchmark problems.•Applied in image segmentation using Multi-level thresholding.

论文关键词：Equilibrium Optimizer,Opposition-based learning,Image segmentation,Optimization,Meta-heuristics

论文评审过程：Received 11 September 2020, Revised 9 November 2020, Accepted 20 February 2021, Available online 24 February 2021, Version of Record 9 March 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.114766