ALGORITHMS FOR ELECTRO-OPTICAL SYSTEMS OF the COMPLEX FOR PROTECTION the RESTRICTED AREAS FROM UNMANNED AERIAL VEHICLES
This article considers approaches to the development of computer vision algorithms for electro-optical systems. The aim of the study is to expand the scope and improve the effectiveness of electro-optical systems in tasks of protecting the closed areas from unauthorized intrusion of unmanned aerial vehicles (UAV). To solve the problems of automatic detection, recognition and auto-tracking of the UAV, a combined optoelectronic system including a wide-field (panoramic) and a narrow-field subsystem of optical-electronic monitoring was developed. The proposed system is a part of specialized complex of means for protection of closed areas, including the means of radio-electronic monitoring, radio-electronic counteraction and operator’s automated workspace. A step-by-step solution of the main image processing and object recognition tasks is considered in detail. From the framework of algorithms of the wide-field subsystem of electro-optical monitoring, an algorithm for reducing optical distortions from the use of wide-angle lenses and an algorithm for automatic object detection in a panoramic image are considered. The task of automatic object detection is divided into two stages. At the first stage, the difference between the current panoramic image and the panoramic image of the background situation is determined, which is formed by the accumulation of panoramic images. At the second stage of the detection algorithm, the author's algorithm for auto-tracking is used to filter and track suspicious zones, determined at the previous stage. This combination of algorithms makes it possible to detect and perform a primary selection of suspicious objects whose angular coordinates are transmitted to a narrow-field electro-optical monitoring subsystem for further analysis. Within the framework of algorithms of a narrow-field subsystem of electro-optical monitoring, the solution of problems of automatic detection, recognition and auto-tracking of objects is considered. The algorithm of multispectral fusion of television and thermal imaging images is described. To solve the problem of automatic recognition of the UAV, it was suggested to use a convolutional artificial neural network. The selected architecture of the artificial neural network showed high classification accuracy and speed of operation. The developed algorithmic framework was tested in the electro-optical systems of the complex of protection of objects from unmanned aerial vehicles and demonstrated high efficiency.