Multi-threshold image segmentation for melanoma based on Kapur's entropy using enhanced ant colony optimization.

ABSTRACT: Melanoma is a malignant tumor formed by the cancerous transformation of melanocytes, and its medical images contain much information. However, the percentage of the critical information in the image is small, and the noise is non-uniformly distributed. We propose a new multi-threshold image segmentation model based on the two-dimensional histogram approach to the above problem. We present an enhanced ant colony optimization for continuous domains (EACOR) in the proposed model based on the soft besiege and chase strategies. Further, EACOR is combined with two-dimensional Kapur's entropy to search for the optimal thresholds. An experiment on the IEEE CEC2014 benchmark function was conducted to measure the reliable global search capability of the EACOR algorithm in the proposed model. Moreove

SUBMITTER: Yang X 

PROVIDER: S-EPMC9663822 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature