Ant colony optimization with horizontal and vertical crossover search: Fundamental visions for multi-threshold image segmentation

作者：

Highlights：

• A novel algorithm called crisscross ant colony optimization (CCACO) is proposed.

• CCACO achieves a great improvement in solution quality and convergence problems.

• The performance of CCACO is verified by comparing with some well-known algorithms.

• CCACO is applied to multi-threshold image segmentation based on 2D histogram.

摘要

•A novel algorithm called crisscross ant colony optimization (CCACO) is proposed.•CCACO achieves a great improvement in solution quality and convergence problems.•The performance of CCACO is verified by comparing with some well-known algorithms.•CCACO is applied to multi-threshold image segmentation based on 2D histogram.

论文关键词：Ant colony optimization,Continuous optimization,Multi-threshold image segmentation,Kapur’s entropy,2D histogram

论文评审过程：Received 7 May 2020, Revised 11 September 2020, Accepted 12 October 2020, Available online 21 October 2020, Version of Record 10 February 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.114122