Image registration using Bacterial Foraging Optimization Algorithm on multi-core processors

In this paper is proposed a parallel approach of the Bacterial Foraging Optimization Algorithm (BFOA) used for image registration (IR) on multi-core processors based systems. IR is an optimization problem computing optimal parameters of the transform to align a source image to a given model by maximizing a similarity measure. IR is an important step in image fusion: the fusion result is affected by the registration result quality. A relatively new registration method is based on the Bacterial Foraging Optimization Algorithm. Depending on the used optimization technique and similarity measure, the IR process may be time consuming. A comparison of the sequential and proposed parallel execution on multi-core systems, for pixel intensity and point feature based registration is presented.