The purpose of the article is to develop a methodology for automating the
detection and selection of moving objects. The detection and separation of
moving objects based on impulse and recurrence neural networks simulation. The
result of the work is a developed motion detector based on impulse and
recurrence neural networks and an automated system developed on the basis of this detector for detecting and separating
moving objects and is ready for practical application. The feasibility of integrating
the developed motion detector with Emgu CV (OpenCV) image processing
package, multimedia framework functions, and DirectShow application programming
interface were investigated. The proposed approach and software for the
detection and separating of moving objects in video images using neural
networks can be integrated into more sophisticated specialized computer-aided
video surveillance systems, IoT (Internet of Things), IoV (Internet of
Vehicles), etc.
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