Image Edge Detection Using Improved Ant Colony Optimization Algorithm
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2013, Vol 2, Issue 11
Abstract
Image processing is a method to convert an image into digital form and perform some operations on it, in order to get an enhanced image or to extract some useful information from it. Image edge detection is the one of the method in the image processing. Edges are significant local changes of intensity in an image. Edges typically occur on the boundary between two different regions in an image. The aim of the edge detection is to extract the important features from edges of images. In this paper, Ant Colony Optimization Algorithm is introduced to tackle the Image edge detection problem. The proposed ACO-based edge detection approach is able to establish a pheromone matrix that represents the edge information presented at each pixel of the image, according to the movements of a number of ants which are dispatched to move on the image. Furthermore, the movements of these ants are riven by the local variation of the images intensity values. Experimental results are provided to demonstrate the superior performance of the proposed approach.
Authors and Affiliations
Thukaram P, S. J. Saritha
Keywords
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