Optimal Transformation Parameter Optimization with Genetic Algorithm in Image Registration Within Hausdorff Distance
Affiliation: Institute of Information Technology, Zhejiang Shuren University, Hangzhou 310015, Zhejiang, China.
As for the sensitivities of traditional Hausdorff distance to the noise and isolated point, which contribute to the
lower matching ratio, this paper puts forward an improved Hausdorff distance model by genetic algorithm to optimize the
transformation parameters. On the basis of a comprehensive analysis of the theory frame from different images matching
techniques, a combined algorithm idea is proposed, using Hausdorff distance as the image measure function and using
genetic algorithm as the search strategy to realize the image registration. Comparison with some recent patents on traditional
algorithm，experiment shows that the improved Hausdorff distance by genetic algorithm can be a very good solution to
robustness problem of the traditional algorithm, and has a higher matching speed in the case of the same edge points of
Keywords: Genetic algorithm, grayscale, hausdorff distance, image registration, isolated point.
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