Thresholding segmentation of skin lesions with modified ant colony optimization algorithm

Image segmentation is the process of breaking up a digital image into many segments, each containing pixels with similar properties. Generally speaking, image segmentation aims to provide an easier-to-analyse and more understandable representation of a picture. Numerous techniques have been presented since this specific topic of picture segmentation was first introduced as a classical issue. The primary content of an image is broken down during the image segmentation process in order to make its representation simpler. Segmenting images involves the separation of pixels into different classes to enable analysis of objects within the image. Multithresholding is a commonly used method for segmentation, but the challenge lies in finding the optimal threshold that accurately segments each image. Metaheuristic methods are high-level procedures that aim to solve optimization problems by searching for acceptable solutions. Recently, researchers have become increasingly interested in using metaheuristics to address image segmentation as an optimization problem. By combining traditional approaches to image segmentation with metaheuristics, researchers have been able to enhance accuracy in various applications.