Performance analysis of Artificial Bee Colony optimization algorithm

In optimization problems, nature inspired algorithms are able to generate near optimal solutions faster than other optimization algorithms. Based on nature intelligence, these algorithms are preferable especially when the function to be optimized is computationally intensive. In this paper it is proposed an image registration procedure based on the Artificial Bee Colony algorithm. First, its performances are compared to those of Particle Swarming and Cuckoo Search algorithms by optimizing some benchmark functions and then by determining the parameters of geometric transforms in image registration procedures.