In the actual process of defect detection of printed matter, there is a problem that the standard printed image and the image to be detected are inaccurately registered due to the camera bracket flutter. Therefore, based on the image de-jitter technique, a motion estimation algorithm combining SURF(speeded-up robust features) and ORB(oriented FAST and rotated BRIEF) is proposed. Firstly, the feature points of the standard printed image and image to be detected are extracted based on the SURF algorithm. Secondly, the extracted feature points are described and matched based on the ORB algorithm. Then, the global motion vectors are obtained by affine model of the correctly matched feature points. Finally, the global motion vector is obtained to compensate the image, and the registration between the image to be detected and the standard printed image is completed. In the experiment, the performance of SURF-ORB, ORB and SIFT(scale-invariant feature transform) motion estimation algorithms are analyzed under three different changes. The motion estimation time of SURF-ORB and ORB is controlled at the millisecond level, which meets the real-time requirement of modern printing defect detection. In addition, SURF-ORB has the largest number of feature points matching, and the matching effect is good. Therefore, in the detection process, from the real-time and accuracy of registration, this method in this paper can accurately and real-time registration of images.