To find the robust matching points between different views on the same object is the key step in a computer vision system in practice.The popular SIFT (Scale Invariant Feature Transforms) has showed its power for robust feature points matching.However,the edge and corner points are not included in the SIFT matching points.Considering the fact that the corner points represent the structure information of an object,we hence propose a robust approach for corner matching via SIFT.This new approach improves the robustness while decreases the computing burden in matching.A series of experiments on corner points matching illustrate that the proposed approach is not sensitive to changes in view,rotation or scale,and robust to noise interference.