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Automatic multi-resolution image registration based on genetic algorithm and Hausdorff distance

机译:基于遗传算法和Hausdorff距离的自动多分辨率图像配准

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摘要

Image registration is a crucial step in all image analysis tasks in which the final information is gained from the combination of various data sources, and it is difficult to automatically register due to the complexity of image. An approach based on genetic algorithm and Hausdorff distance to automatic image registration is presented. We use a multi-resolution edge tracker to find out the fine-quality edges and utilize the Hausdorff distance between the input image and the reference image as similarity measure. We use wavelet decomposition and genetic algorithm, which combine local search methods with global ones balancing exploration and exploitation, to speed up the search of the best transformation parameters. Experimental results show that the proposed approach is a promising method for registration of image.
机译:图像配准是所有图像分析任务中的关键步骤,在这些步骤中,最终信息是从各种数据源的组合中获得的,并且由于图像的复杂性,很难自动配准。提出了一种基于遗传算法和Hausdorff距离的图像自动配准方法。我们使用多分辨率边缘跟踪器找出高质量边缘,并将输入图像和参考图像之间的Hausdorff距离用作相似性度量。我们使用小波分解和遗传算法,将局部搜索方法与平衡探索和开发的全局搜索方法相结合,以加快最佳转换参数的搜索速度。实验结果表明,该方法是一种有前景的图像配准方法。

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