曲率形状表示与遗传算法的图像配准

Xiang Zhang, Changjiang Zhang
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引用次数: 0

摘要

针对图像特征点匹配问题,提出了一种新的特征点提取方法。该方法基于曲率尺度空间(CSS)的角点检测方法。该方法可以准确提取不同位置和方向的图像角点。为了精确匹配两幅图像的角点,采用一种综合了两个匹配角点的角度差、灰度差、相对距离和归一化相关系数的整体限制条件来提高匹配精度。最后,采用遗传算法获得最优配准参数。利用最优配准参数对两幅图像进行精确匹配。实验结果表明,该方法能准确匹配图像,优于传统的图像配准方法。
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Image Registration by Curvature Shape Representation and Genetic Algorithm
A new feature point extraction method for the image feature point matching is proposed. The proposed method is based on the corner detection method with curvature scale space (CSS). This method can accurately extract the image corner points in different positions and directions. In order to accurately match the corner points of two images, an overall restricted condition, which combines angle difference, gray level difference, relative distance and normalized correlation coefficient of the two matched corner points, is used to improve the matching accuracy. Finally, genetic algorithm is used to obtain the optimal registration parameters. The optimal registration parameters are used to accurately match the two images. The experimental results show that the proposed method can accurately match the images and better than traditional image registration method.
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