基于SIFT特征的眼底图像自动拼接

针对眼底图像对比度低、不同视场的图像间存在几何畸变等特点，提出一种基于SIFT特征的眼底图像自动拼接算法。该算法分别提取待拼接眼底图像的SIFT特征点，并用向量进行描述，确定两幅图像特征点的匹配关系，使用MLESAC算法去除误匹配点对，提出对特征点对提纯的距离-斜率相似测度方法，计算匹配点之间的透视变换矩阵，最后进行图像配准和拼接。对实际眼底照相机获取的多幅图像拼接结果表明，该算法具有很好的鲁棒性和稳健性，可以实现眼底图像的高精度自动拼接。

Automatic fundus images mosaic based on SIFT feature

In this paper, a SIFT feature based fundus image automatic mosaic algorithm is presented, according to the characteristics of low contrast and the geometric distortion between different fields of the view of the fundus image. The SIFT features of fundus images are extracted and described using vector to determine the feature points matching between two images, and outlier points are removed using MLESAC algorithm. A distance-slope similarity measure method is put forward to purify feature points, then the perspective transformation matrix is computed according to matching points between images, and image registration and image mosaic is implemented finally. The mosaic results of multiple images obtained by fundus camera show that the algorithm has good robustness and stability, and high-precision automatic fundus image mosaic can be achieved.