Journal of Advanced Defense Science & Technology

Journal of Advanced Defense Science & Technology

Conceptual Design of Intelligent Detection/Tracking System of Out-of-Control Radioactive Material in Crowded Radiation Incidents: Integration of Machine Vision Data and Multi-Detector System

Document Type : -

Authors
AmirMohammad Beigzadeh
Hadi Ardiny
Mohsen Mehrabi
Assistant Professor, Nuclear Science and Technology Research Institute, Atomic Energy Organization, Tehran, Iran
Abstract
Nuclear technology is advancing rapidly worldwide, but the presence of radioactive materials poses significant risks to society and the environment. These risks are exacerbated by threats such as terrorism, mishandling, and the illegal transportation of these substances. Consequently, there is an urgent need to enhance detection and tracking systems for radioactive materials to strengthen security and prevent potential terrorist acts. This study introduces a novel approach to radiation mapping and detection through the development of machine vision algorithms and multi-detection system modeling. The goal is to improve the efficiency and accuracy of identifying and locating uncontrolled radioactive sources in complex environments using contemporary machine vision techniques. The proposed tracking method is based on the KLT (Kanade-Lucas-Tomasi) algorithm. The system captures and processes moving images in real time while tracking object movement paths and recording radiation data from the detector. By integrating spatial data with radiation data, the system can accurately differentiate uncontrolled radioactive sources from other moving objects. Incorporating these advanced algorithms into existing radiation detection systems has the potential to significantly mitigate the risks associated with radiation incidents.
Keywords
Radioactive sources
Image processing
Machine vision
Monte Carlo
Tracking
Radiation event
Detection
Nuclear radiation
Subjects
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Journal of Advanced Defense Science & Technology
Volume 15, Issue 2 - Serial Number 56
Summer
Summer 2024
Pages 107-117

  • Receive Date 20 May 2024
  • Revise Date 01 July 2024
  • Accept Date 10 August 2024
  • Publish Date 22 August 2024