UAV is now widely used for aerial image acquisition, transmission and recognition. One of the UAV images research object is target identification. In this thesis proposed an algorithm for target identification based on new feature descriptors. The new descriptors are result of the Dominate Orientation of Subregions, so called DOOS. In this algorithm after detecting target and scene image keypoints and describing them by DOOS, corresponding keypoints between to image is discovered. By RANSAC algorithm removed the outlier and affine transform is estimated. At the end by affine transform, target location is found in target image. The experiments show that DOOS descriptors are more robust than SIFT and BRISK. In additional, because of the low dimensionality and structure of DOOS descriptors, matching of them is faster than other descriptors like SIFT and SURF. We propose a simple implementation for matching DOOS descriptor to show it is easy to implement on D and FPGAs. Keywords: Target Identification, DOOS descriptor, SIFT, Aerial images.
