Color image segmentation based on multi-level Tsallis–Havrda–Charvát entropy and 2D histogram using PSO algorithms

作者：

Highlights：

• A generalized 2D multi-level thresholding criterion function is proved rigorously by mathematical induction method.

• A multi-level thresholding scheme for a RGB color image is proposed.

• PSO algorithm is applied to seek to optimal threshold values in a very reasonable computational time.

• The segmented image is compared with the human segmentation from BSDS300 to evaluate the experiment results quantitatively and objectively.

摘要

•A generalized 2D multi-level thresholding criterion function is proved rigorously by mathematical induction method.•A multi-level thresholding scheme for a RGB color image is proposed.•PSO algorithm is applied to seek to optimal threshold values in a very reasonable computational time.•The segmented image is compared with the human segmentation from BSDS300 to evaluate the experiment results quantitatively and objectively.

论文关键词：Color image segmentation,Multi-level thresholding,Two-dimensional histogram,Tsallis–Havrda–Charvát entropy,PSO

论文评审过程：Received 17 August 2017, Revised 16 May 2018, Accepted 18 March 2019, Available online 19 March 2019, Version of Record 28 March 2019.

论文官网地址：https://doi.org/10.1016/j.patcog.2019.03.011