Automatic Threshold Selection Based on Artificial Bee Colony Algorithm

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 objects from the background, which is one of the most popular algorithms. The artificial bee colony algorithm (ABC) is a recently presented meta-heuristic algorithm, which has been successfully applied to solve many optimization problems. As a matter of fact the classical Otsu threshold selection can be viewed as an optimization problem. Hence, this paper introduces a new method to select image threshold automatically based on ABC algorithm. In the end, the proposed method has been implemented and tested on several images. Experiments results show that proposed method performs well which is a feasible method to help select optimum threshold.