Aiming at the problems of scale change, illumination change and noise interference in the uppers matching, a shoe upper matching detection method based on the speeded-up robust features-object request broker (SURF-ORB) algorithm combined with random sample consensus (RANSAC) algorithm is presented. The feature points of the uppers image are extracted by SURF. The descriptors are obtained and the feature points are described by the ORB algorithm. In order to obtain more accurate matching points, the initial matching is completed by using the Hamming distance, and then by combining the RANSAC algorithm, the mismatching points generated by noise interference and illumination changes are eliminated. The experimental results show that the algorithm can effectively match and has strong robustness when there are scale change, illumination change and noise interference in the shoe uppers image.