As a popular evolutionary algorithm, Artificial Bee Colony (ABC) algorithm has been
successfully applied into threshold-based image segmentation. Due to its one dimension …

Multilevel-thresholding is an efficient method used in image segmentation. This paper
presents a hybrid meta-heuristic approach for multi-level thresholding image segmentation …

This paper explores the use of the Artificial Bee Colony (ABC) algorithm to compute
threshold selection for image segmentation. ABC is an evolutionary algorithm inspired by …

Image threshold segmentation based on artificial bee colony algorithm (ABCA) and
maximum entropy is presented in this paper. The entropy function is simplified with several …

The goal of image segmentation is to cluster pixels into salient image regions, it is the most
significant step in image analysis. Thresholding is a simple but effective tool to separate …

Image segmentation is still a crucial problem in image processing. It hasn yet been solved
very well. In this study, we propose a novel multi-level thresholding image segmentation …

Multi-level thresholding is one of the essential approaches for image segmentation.
Determining the optimal thresholds for multi-level thresholding needs exhaustive searching …

Multilevel thresholding has been one of the most popular image segmentation techniques;
however, most of these techniques are time-consuming. This paper proposes a cooperative …

This paper proposes a modified artificial bee colony optimizer (MABC) by combining bee‐to‐
bee communication pattern and multipopulation cooperative mechanism. In the bee‐to‐bee …

The artificial bee colony algorithm (ABC) has been successfully applied to various
optimization problems, but the algorithm still suffers from slow convergence and poor quality …