  This paper describes the application of a real coded genetic algorithm (GA)
to align two or more 2-D images by means of image registration. The proposed
search strategy is a transformation parameters-based approach involving the
affine transform. The real coded GA uses Simulated Binary Crossover (SBX), a
parent-centric recombination operator that has shown to deliver a good
performance in many optimization problems in the continuous domain. In
addition, we propose a new technique for matching points between a warped and
static images by using a randomized ordering when visiting the points during
the matching procedure. This new technique makes the evaluation of the
objective function somewhat noisy, but GAs and other population-based search
algorithms have been shown to cope well with noisy fitness evaluations. The
results obtained are competitive to those obtained by state-of-the-art
classical methods in image registration, confirming the usefulness of the
proposed noisy objective function and the suitability of SBX as a recombination
operator for this type of problem.
