Evolutionary Multi-level Thresholding for Breast Thermogram Segmentation

In the pre-processing of the digital thermograms, multi-level thresholding plays a crucial role in the segmentation of thermographic images for better clinical decision support. This paper attempts to optimize the multi-level thresholding method for thermographic image segmentation using Differential Evolution (DE) with the Otsu's between class variance. We have compared the results of the proposed method with the other popular metaheuristics- PSO, GWO and WOA. We have applied the Wilcoxon rank-sum test for the performance evaluation.

Automated summary

This paper aims to optimize the multi-level thresholding method for thermographic image segmentation using Differential Evolution (DE) with the Otsu's between class variance. Results were compared with other popular metaheuristics, and performance was evaluated using the Wilcoxon rank-sum test.