Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran
Targets and objects registration and tracking in a sequence of images play an important role in various areas. One of the methods in image registration is feature-based algorithm which is accomplished in two steps. The ﬁrst step includes ﬁnding features of sensed and reference images. In this step, a scale space is used to reduce the sensitivity of detected features to the scale changes. Afterward, we attribute feature points that obtained in the ﬁrst step, descriptions using brightness value around the feature points. In this paper, a new algorithm is proposed based on Binary Robust Invariant Scalable Keypoints (BRISK) and Scale Invariant Feature Transform (SIFT) algorithms. The proposed algorithm uses the directional pattern to describe the edges which are around the keypoints. This pattern is perpendicular to the direction of keypoints which shows the direction of the edge and provides more useful information regarding brightness around the feature point to make descriptor vector. Furthermore, in the proposed algorithm, the output vector consists of multilevel values instead of binary values which means further useful information is involved in the descriptor vector. Also, levels of output vectors can be adjusted using a single parameter so that the processor with low computing ability can tune the output to a binary vector. Experimental results show that the proposed algorithm is more robust than the BRISK algorithm and the eﬃciency of the algorithm is about the same as BRISK algorithm.