Detection of Unmanned Aerial Vehicles Using Computer Vision Methods: A Comparative Analysis

Abstract

Detection of small objects in the airspace is a crucial task in the military. In the era of today’s unmanned aerial vehicles (UAVs) technology, many military units are exposed to recognition and observation through flying objects. They are often equipped with optoelectronic warhead making a way to collect essential and secret data of the military unit. Modern technical solutions make it possible to implement some methods facilitating detection of flying objects. A lot of them utilize computer vision techniques based on image processing algorithm. Therefore, in this article, we present an analysis of the most promising algorithm for detection of small flying objects.

Tracking of Unmanned Aerial Vehicles Using Computer Vision Methods: A Comparative Analysis

“…The detection step often utilises advanced object detection algorithms, implemented in computer vision libraries. In [13], the comparative analysis of these algorithms, applied in the OpenCV libraries, was performed. The algorithms were divided into two main groups -supervised classifiers, and background subtractors.…”

“…The first group included algorithms, such as the KNN, Codebook, and Codebook 2, while the second group comprised the MOG, MOG2, and GMG. According to the research, the MOG algorithm was the best choice for UAVs detection [13].…”