An edge detection technique using hybrid Ant Colony Optimization-genetic algorithm

In this paper, an image edge detection technique based on the ant colony system (ACS) is implemented. ACS is one of the many ant algorithms of Ant Colony Optimization (ACO). The number of artificial ants, the total step number for each ant and the size of ant memory used in ACS is determined by applying genetic algorithm. Several reproductions of input image are obtained by nonlinear contrast enhancement applied to the input image. More than one image is passed through ACS and the outputs are integrated onto each other to generate one output image. A global threshold is applied to this very last image in order to obtain binary edge image.