M. P. Mukhina, Yu. V. Trach, A. P. Prymak


A great deal of features detectors and descriptors are proposed nowadays for various computer vision applications. The task of image processing which is invariant to all weather conditions (such as rain, fog, smoke, unfavorable lights, camera rotation) is presented. The influence of weather conditions on the number of determined key points in the image is analyzed, and how certain unfavorable conditions influence the tracking of these points from frame to frame. Two binary descriptors are considered for finding special points of the image; BRIEF (Binary robust independent elementary features) and ORB (Oriented FAST and rotated BRIEF) descriptors, as well as their modifications, to explore the most efficient descriptor which can be used in applications that run in real time. The result of the study shows that the descriptors have high stability characteristics, working with different types of images and rotation angles, using the recommendations for the use of their modifications.


Object recognition; binary descriptors, interest points, key points; descriptors, detectors


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