An augmented reality image registration method based on improved ORB

Abstract

Abstract In the process of Augmented Reality (AR) image registration, the traditional ORB (oriented FAST and rotated BRIEF) algorithm has low registration rate and poor real-time performance. In this paper, an improved AR image registration method based on improved ORB is proposed. Firstly, the calibration image and video frame image feature points are obtained by the improved FAST feature detection algorithm. Then, the binary descriptor of BRISK, which using the custom domain sampling pattern is used for feature description, and the scale invariance of the traditional ORB algorithm is improved. Finally, the random sampling consistency (RANSAC) algorithm is used to eliminate the wrong matching point pairs and optimize the feature matching. Experiments show that compared with the AR image registration method described by the traditional ORB algorithm and the FREAK feature, the registration rate of the proposed algorithm is increased by 1.1% and 8.4%, and the generation time is reduced by 0.13s and 0.12s, respectively. The experimental results show that the AR image registration method proposed in this paper can obtain higher feature point registration rate, and has better real-time performance, which can better meet the application needs of AR image registration.