An improved RANSAC algorithm using within-class scatter matrix for fast image stitching is proposed in this paper. First, features described by SIFT are extracted. Next, the Min-cost K-flow algorithm is used to match SIFT points in different images. Then, the improved RANSAC algorithm with the within-class scatter matrix is used to divide the matching feature points into two classes: inliers and outliers. Finally, the homography is computed in the set of inliers. Experiment results show that the improved algorithm can increase the registration speed by some 20 percent with the same accuracy and robustness comparing to the original RANSAC algorithm.© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.