基于FAST角点检测的图像配准算法

Image Registration Algorithm Based on Fast Corner Detection

提出了一种具有类SIFT描述特征的FAST角点检测的图像配准算法。先利用FAST对图像进行特征点提取;然后,采用圆环结构算子对提取出的特征点进行类SIFT的特征描述;最后,通过K-D算法将提取出来的特征点进行粗匹配,并使用视差梯度进行预筛选,使用RANSAC算法提纯,从而实现特征点匹配。试验结果表明,与SIFT算法和改进的SIFT算法相比,本算法减少了误匹配的数目,提高了匹配的精确性和稳定性。

Proposes an image registration algorithm of FAST corner detection with the description of the characteristics of SIFT. First applies FAST to extract image feature points, then uses the ring structure operator for SIFT description of the feature points, finally conducts coarse matching of the points by means of K-D algorithm, and pre screening through disparity gradient and purification with RANSAC algorithm achieves feature points matching. The experimental results show that compared with SIFT algorithm, the improved SIFT algorithm reduces the number of false matches and improves the accuracy and stability of matching.