An efficient multilevel thresholding segmentation method for thermography breast cancer imaging based on improved chimp optimization algorithm
作者：
Highlights：
• Improved Chimp Optimization Algorithm using Opposition-based Learning and Lévy Flight.
• Evaluate IChOA to solve the Multi-level Thresholding Cancer Segmentation Imaging.
• The efficiency of the algorithm is evaluated using Otsu and Kapur methods.
• Verify the segmentation quality using the PSNR, SSIM, FSIM.
• The quality of the segmentation results is better than other competitor algorithms.
摘要
•Improved Chimp Optimization Algorithm using Opposition-based Learning and Lévy Flight.•Evaluate IChOA to solve the Multi-level Thresholding Cancer Segmentation Imaging.•The efficiency of the algorithm is evaluated using Otsu and Kapur methods.•Verify the segmentation quality using the PSNR, SSIM, FSIM.•The quality of the segmentation results is better than other competitor algorithms.
论文关键词：Breast cancer,Chimp optimization algorithm,Image segmentation,Kapur’s and Otsu’s method,Multi-level thresholding,Thermography images,Meta-heuristics
论文评审过程：Received 1 January 2021, Revised 20 May 2021, Accepted 21 July 2021, Available online 30 July 2021, Version of Record 4 August 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115651
