SVM-GA Based A Novel Technique for the Detection of the Vehicle in an Optimized Overlapped Multi-Camera System

Authors

  • Joshi Rakhi Madhukaro Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Hyderabad-500075, Telangana, India
  • D. S. Rao Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Hyderabad-500075, Telangana, India

Keywords:

CCTV, FOV, GA-genetic algorithm, Multi-Camera setup, machine learning, SVM, vehicle detection, Video Surveillance, neural network

Abstract

The presence of CCTV cameras on highways helps enhance public safety and instills a sense of security among road users. It promotes responsible behavior, discourages reckless driving, and can aid in resolving disputes related to accidents or incidents. This research proposes an innovative and very trustworthy approach to identify vehicles on the road. This paper also examines vehicle tracking in the presence of uncalibrated Cameras with overlapping fields of view used to capture images, which are characteristics of traffic surveillance systems. To discover a greater accuracy of the desired field of vision in such a situation, it is crucial to create and construct a system to compute the road geometry and establish correspondence between the positions of the multiple cameras. We outline a special technique for automatically identifying traffic camera angle positions using a collection of dimensions and the GA-SVM machine learning algorithm followed by the novel vehicle detection architecture.

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Published

25.12.2023

How to Cite

Madhukaro, J. R. ., & Rao, D. S. . (2023). SVM-GA Based A Novel Technique for the Detection of the Vehicle in an Optimized Overlapped Multi-Camera System . International Journal of Intelligent Systems and Applications in Engineering, 12(1), 810–818. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4194

Issue

Vol. 12 No. 1 (2024)

Section

Research Article

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