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Image registration (IR) aims to find a transformation between two or more images acquired under different conditions. This problem has been established as a very active research field in computer vision during the last few decades. IR has been applied to a high number of real-world problems ranging from remote sensing to medical imaging, artificial vision, and computer-aided design. Recently, there is an increasing interest on the application of the evolutionary computation paradigm to this field in order to solve the ever recurrent drawbacks of traditional image registration methods as the iterated closest point algorithm. Specially, evolutionary image registration methods have demonstrated their ability as robust approaches to the problem. Unlike classical IR methods, they show the advantage of not requiring a good initial estimation of the image alignment to proceed. In this contribution, we aim to review the state …