Feature matching is one of the key steps in image mosaic. The matching algorithm based on the best of two nearest matches often has a large number of mismatches. The good filtering algorithm can reduce the mismatch rate and improve the processing efficiency. Therefore, it is of great significance to study this kind of algorithm. The RANSAC algorithm is a widely used filtering algorithm, but it has many defects such as uncertain number of iterations and none of self-adaption in BA process. In this study, we propose a new filtering algorithm of Feature Matching based on Local Clustering (LCMF). The feature points are extracted by SURF and ORB, the BestOf2NearestMatcher algorithm is used to match, and then the LCMF algorithm is used to filter. The experiment shows that the algorithm can get better filtering result when ORB is used to extract feature.