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

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1 تهران-امیرآباد شمالی-سازمان انرژی -پژوهشگاه علوم و فنون هسته ای -پژوهشکده کاربرد پرتوها

2 Assistant Professor, Research Institute of Nuclear Sciences and Technologies, Radiation Application Research School, Atomic Energy Organization of Iran, Tehran, Iran

Abstract

Nuclear technology is expanding rapidly around the globe; however, the presence of radioactive materials poses significant risks to human societies and the environment. These dangers are exacerbated by threats such as terrorism, mishandling, and the illegal transport of these substances. Consequently, there is an urgent need to enhance detection and tracking systems for radioactive materials. Advancements in this field will bolster security and help prevent terrorist acts. This study introduces a novel approach for ray mapping and detection through the development of machine vision algorithms and the modeling of multi-detection systems. The objective is to improve the efficiency and accuracy of identifying and locating out-of-control radioactive sources in complex and dynamic environments using contemporary machine vision techniques. The tracking method employed is based on the KLT (Kanade-Lucas-Tomasi) algorithm. The designed system simultaneously captures and processes moving images while detecting the movement paths of objects, all while recording beam data in the detector. Ultimately, by integrating spatial data with radiation data, the system can accurately identify out-of-control radioactive sources among other moving objects. The incorporation of these algorithms into existing radiation detection systems has the potential to significantly mitigate the risks associated with radiation incidents.

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History

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

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