Automatic fundus images mosaic based on SIFT feature
基于SIFT特征的眼底图像自动拼接

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.