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In many image-processing applications it is necessary to register multiple images of the same scene acquired by different sensors, or images taken by the same sensor but at different times. Mathematical modeling techniques are used to correct the geometric errors like translation, scaling and rotation of the input image to that of the reference image, so that these images can be used in various applications like change detection, image fusion etc. In the conventional methods, these errors are corrected by taking control points over the image and these points are used to establish the mathematical model. This paper addresses the image registration problem applying genetic algorithms. The image registration's objective is to define mapping that best match two set of points or images. In this work the point matching problem was addressed employing a method based on nearest-neighbor. The mapping was handled by affine transformations[4].

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