Abstract: In order to solve the problem that it is difficult to balance the real-time performance and robustness in image matching using local feature,a fast image matching algorithm based on Harris operator is presented.By analyzing the basic theory of Harris operator,it is proposed that local feature can be described with the temporary data of feature detecting.Furthermore,a low dimensions feature descriptor is built with the trace of Harris autocorrelation matrix,which can both preserve the robustness and reduce the computation effectively.Finally,the absolute distance between descriptors is used as a similarity measurement to match feature points for decreasing the computing complexity.Simulation results indicate that the proposed algorithm keeps invariant in the case of image zoom,rotation,blurring,luminance varying as well as smaller viewpoint changes,and its speed is faster.