基于改进ORB算法的虚实注册方法

针对增强现实(AR)中虚实注册的精度和实时性易受图像纹理和不均匀光照影响的问题，提出一种改进的ORB算法予以解决。首先，设置ORB特征点数量和距离阈值对图像特征点稠密区域进行优化，利用并行算法保留特征值较大的N个特征点；然后，采用离散差异特征增强光照不均匀变化时的稳定性，将改进的ORB与词袋(BOF)模型结合，实现基准图像的快速检索；最后，利用图像间的单应性关系实现虚实注册。从准确性和实时性两方面对提出的改进ORB算法与原始ORB算法、尺度不变特征变换(SIFT)算法和加速稳健特征(SURF)算法进行了对比实验分析，结果显示改进ORB算法的注册时间平均降低了约40%，准确性达到了95%以上。实验结果表明，所提出的算法在不同纹理和不均匀光照的情况下，具有更高的实时性、准确性。

Virtual-real registration method based on improved ORB algorithm

Aiming at the problem that virtual-real registered accuracy and real-time performance are influenced by image texture and uneven illumination in Augmented Reality (AR), a method based on improved ORB (Oriented FAST (Features from Accelerated Segment Test) and Rotated BRIEF (Binary Robust Independent Elementary Features)) algorithm was proposed to solve it. The method firstly optimized the dense region of image feature points by setting the number and distance threshold of it and used parallel algorithm to reserve N points of greater eigenvalue; Then, the method adopted discrete difference feature to enhance the stability of uneven illumination changes and combined the improved ORB with BOF (Bag-of-Features) model to realize quick retrieval of Benchmark image. Finally, it realized the virtual-real registration by using the homographics between images. Comparative experiments among the proposed method, original ORB, Scale Invariant Feature Transform (SIFT) and Speed Up Robust Features (SURF) algorithms were performed from the aspects of accuracy and efficiency, and the proposed method reduced the registration time to about 40% and reached the accuracy more than 95%. The experimental results show that the proposed method can get a better real-time performance and higher accuracy in different texture and uneven illumination.