For image registration, point matching is still a fundamental problem because of the complex distortion such as transformation, missing and irrelevant points involved in two point sets detected from images. In this paper, a new method based on Genetic Algorithm (GA) is proposed to find the optimal affine transformation between two different point sets. In order to deal with the influence of the missing and spurious points, we define a fitness function in the combination of global topology of point set and individual point property. The experimental results on randomly generated 2D point sets demonstrate that the proposed GA-based point matching algorithm can achieve good performance in terms of correct matching (CM), false matching (FM), and missing matching (MM).
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