Algorithm for Recognition of Movement of Objects in a Video Surveillance System Using a Neural Network

Author:

Harish S.1,Anil Kumar C.1,Shrinivasan Lakshmi2,Rohith S.3,Asfaw Belete Tessema4ORCID

Affiliation:

1. Department of Electronics and Communication Engineering, R. L. Jalappa Institute of Technology, Kodigehalli, Doddaballapur, Karnataka 561203, India

2. Department of Electronics and Communication Engineering, Ramaiah Institute of Technology, Bengaluru, Karnataka 560054, India

3. Department of Electronics and Communication Engineering, Nagarjuna College of Engineering and Technology, Bengaluru, Karnataka 562164, India

4. Department of Chemical Engineering, Haramaya Institute of Technology, Haramaya University, Haramaya, Ethiopia

Abstract

The aim of this article is to address the problem of protecting the private property of a protected object, namely: we propose an algorithm for detection of object movements by means of a neural network for the video surveillance system. Consistency of perception of the external world in the form of images allows for the investigation of properties of the limited number of objects on the basis of familiarization with their final number. Based on the literature analysis, the main definitions of the theory of image recognition were established, such as “image,” “sign,” and “vector realization.” A comparison is made of approaches, methods, and technologies for recognizing the movement of objects, and their strengths and weaknesses are discussed. It was found that the neuron network is the most effective method for solving the problem of recognition of the movement of objects due to the accuracy of the result, simplicity, and speed. On the basis of the structural scheme of the complex algorithm of processing and analysis of images, the algorithm for recognition of the motion of objects by means of a neural network for the system of video observation is developed.

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Hardware and Architecture,Mechanical Engineering,General Chemical Engineering,Civil and Structural Engineering

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Machine Learning-Based Pattern Recognition Models for Image Recognition and Classification;Lecture Notes in Networks and Systems;2024

2. Research on Secure Interactive System of Video Surveillance Data;2023 IEEE 12th International Conference on Communication Systems and Network Technologies (CSNT);2023-04-08

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