Implementation of Multilevel Thresholding Based Ant Colony Optimization Algorithm for Edge Detection of Images

Abstract

Edges in an image characterize object boundaries in an image, which is helpful in image processing and feature extraction in a particular scene. One of the methods used to detect edges in an image is image thresholding, which replaces a pixel in an image with black pixel if an image intensity is less than some constant T. Edge detection is used to classify, interpret and analyze the digital images in various fields such as robots, the sensitive applications in military, etc. A hierarchical multilevel thresholding method for edge detection using the Ant Colony algorithm is used in this paper. Multilevel thresholding technique is applied in this paper based on previous work done by Ashour, A. S., El-Sayed (2014). Further, the results are produced for edge detection of images using ACO algorithm with multilevel thresholding. Both Gray scale images and color images are used to evaluate the efficiency of the algorithm.