关键词: 特征匹配, 二进制特征描述算法（ORB）, 尺度空间, 特征主方向, 梯度方向

Abstract: To solve the problem of large scale registration error and low rate of registration in binary description algorithm, this paper proposes an improved ORB feature matching algorithm with scale and direction. The algorithm uses the binary description algorithm ORB as the basis to construct a pyramid scale space, improve the scale space structure, simplify the number of scale space layers and the number of sampled images, make the process of extracting feature points more efficient, and Harris function is used to detect features, eliminate the influence of edge feature points, and extract feature points with scale information. Then, the method of gradient direction statistics is used to replace the way of computing the main direction by the gray-scale centroid method in the traditional ORB algorithm. The main direction of the neighborhood range is optimized and the accuracy of the image feature main direction is improved. The experimental results show that the improved ORB algorithm greatly improves the performance of scale and rotation registration, and the accuracy of registration is higher than the traditional ORB, and it can better meet the requirements of fast and accurate registration of complex images.

Key words: feature matching, Oriented fast and Rotated Brief（ORB） algorithm, scale space, feature main direction, gradient direction