Year: 2024
Type: conference-paper
Abstract: A method for recognizing the contours of objects in a video data stream is proposed. The data will be uploaded using the video camera. Objects will be recognized in real-time. We will use YOLO—a method of identification and recognition of objects in real-time. Recognized objects will be recorded in a video sequence showing the contours of the objects. The approach proposed in the project reasonably synthesizes methods of artificial intelligence, theories of computer vision on the one hand, and pattern recognition on the other; it makes it possible to obtain control influences and mathematical functions for decision-making at every moment with the possibility of analyzing the influence of external factors and forecasting the flow of processes and refers to the fundamental problems of mathematical modeling of real processes. The installation of the neural network is shown in detail. The characteristics of the neural network and its capabilities are shown. Approaches to computer vision for object extraction are shown. Well-known methods are methods of expanding areas, methods based on clustering, contour selection, and methods using a histogram. The work envisages building a system for rapid identification of combat vehicles based on the latest image filtering methods developed using deep learning methods. The time spent on machine identification will be 10–20% shorter, thanks to the developed new information technology for detecting objects in conditions of rapidly changing information.
Institutions: Lviv Polytechnic National University, Lviv University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W7166345417