Robust binary feature point descriptor

In order to improve the speed of feature point matching, a binary method is used to generate feature point description, and the descriptor's adaptability to different scales and rotations is improved. The descriptor is computed using intensity difference tests. The descriptor similarity is evaluated by using Hamming distance, and the time performance of the algorithm is improved by binary operation. The Wall and Graffiti image sets as well as their transformed image sets are used to test the performance of the proposed algorithm for the different perspectives, rotations and scales. The matching accuracies on each image set are obtained. The comparison results of the proposed algorithm and the speeded up robust feature(SURF) algorithm show that during the feature point matching between the two images, the construction time and the matching time of the descriptors of the proposed algorithm are 1043.67 and 4313.36 ms, respectively, while the corresponding data of the SURF algorithm are 3950.34 and 9951.03 ms, indicating that the time characteristics of the proposed algorithm are better than those of the SURF algorithm. In addition, on most image sets, the matching accuracy of the proposed algorithm is higher than that of the SURF algorithm.