Image Thresholding Using Ant Colony Optimization

Abstract

This study is an investigation of the application of ant colony optimization to image thresholding. This paper presents an approach where one ant is assigned to each pixel of an image and then moves around the image seeking low grayscale regions. Experimental results demonstrate that the proposed ant-based method performs better than other two established thresholding algorithms. Further work must be conducted to optimize the algorithm parameters, improve the analysis of the pheromone data and reduce computation time. However, the study indicates that an ant-based approach has the potential of becoming an established image thresholding technique.