In terms of the application of Harris algorithm, since the less real-time and a large amount of computation together with poor anti-noise ability and other issues, an improved corner detection algorithm is proposed based on the Harris, combing the local weighted entropy with minimum intensity change (MIC) algorithm. First of all, the candidate corner point set is computed through the local weighted entropy algorithm. Then the candidate corner is divided into three categories according to the corner response function (CRF) value of Harris algorithm. Finally, the best matching corners are obtained through the adaptive template and MIC algorithm of the threshold. Experimental results show that the proposed algorithm can improve the real-time of the original algorithm, increase the quantity of the corner extraction with better accuracy, and remove the most false corners effectively.