Visual Object Recognition System

Authors

DOI:

https://doi.org/10.18372/1990-5548.73.17007

Keywords:

video surveillance, automation, keypoint, feature deteсtion, contour, contour detection

Abstract

This article introduces the problem of object detection and recognition. The potential mobility of this solution, ease of installation and ease of initial setup, as well as the absence of expensive, resource-intensive and complex image collection and processing systems are presented. Solutions to the problem are demonstrated, along with the advantages and disadvantages of each. The selection of contours by a filter based on the Prewitt operator and a detector of characteristic points is an algorithm of the system, developed within the framework of object recognition techniques. The reader can follow the interim and final demonstrations of the system algorithm in this article to learn about its advantages over traditional video surveillance systems, as well as some of its disadvantages. A webcam with a video frame rate of 25 frames per second, a mobile phone and a PC with the Matlab2020 programming environment installed (due to its convenience and built-in image processing functions) are required to illustrate how the system works.

Author Biographies

Mykola Vasylenko , National Aviation University, Kyiv

Candidate of Science (Engineering). Senior lecturer

Aviation Computer-Integrated Complexes Department

Faculty of Air Navigation Electronics and Telecommunications

Maksym Haida , National Aviation University, Kyiv

Bachelor

Aviation Computer-Integrated Complexes Department

Faculty of Air Navigation Electronics and Telecommunications

References

A system for detecting and recognizing moving biological objects for unmanned vehicles based on intelligent edge computing / m. A. Al-Sveity et al. Electrosvyaz 2021, no. 9(22).

https://doi.org/10.34832/elsv.2021.22.9.004 (date of access: 18.11.2022).

Gepard_vvk. Algoritmy vydeleniya konturov izobrazheniy. Habr https://habr.com/ru/post/114452/ (date of access: 18.11.2022).

Car Number Plate Detection Using MATLAB and Image Processing. Circuit Digest – Electronics Engineering News, Latest Products, Articles and Projects. URL: https://circuitdigest.com/tutorial/vehicle-number-plate-detection-using-matlab-and-image-processing (date of access: 18.11.2022).

Repository BNTU – Repository BNTU. URL: https://rep.bntu.by/bitstream/handle/data/27161/Vosstanovlenie_kontrasta_polutonovogo_izobrazheniya_v_pakete_MATLAB.pdf?sequence=1&isAllowed=y (date of access: 18.11.2022).

M. P. Mukhina, "Algorithm of Visual Tracking of Contrast Moving Objects," Of the Third World Congress “Aviation in The XXI-st Century,” 2008.

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Published

2022-11-24

How to Cite

Vasylenko , M., & Haida , M. (2022). Visual Object Recognition System. Electronics and Control Systems, 3(73), 9–19. https://doi.org/10.18372/1990-5548.73.17007

Issue

Vol. 3 No. 73 (2022)

Section

COMPUTER SCIENCE

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