Document Type : Research
Authors
1 Radiation Application Research School, Nuclear Science & Technology Research Institute, Tehran, Iran
2 Assiatance Professor, Radiation Application Research School, NSTRI, Tehran, Iran
Abstract
Nuclear technology is rapidly expanding worldwide. However, radioactive materials pose a big risk to human societies and the environment. This is due to threats from terrorism, misuse, or unauthorized movement. Thus, we need to improve radioactive source detection and tracking systems. This will boost security and stop terrorist actions. This paper introduces a novel approach for beam mapping and detection by employing machine vision algorithms and modeling nuclear detection systems that incorporate scintillating crystal detectors and photomultiplier tubes. The primary objective is to enhance the efficiency and accuracy in identifying and locating out-of-control radioactive sources within complex and dynamic environments through the utilization of modern machine vision techniques. The tracking method employed in this approach is based on the Kanade-Lucas-Tomasi (KLT) method. The developed system simultaneously acquires and processes moving images for detecting the trajectory characteristics of objects, while recording radiation data using the detector. By effectively combining spatial and radiation data with high precision, the out-of-control radioactive source is successfully identified amidst other moving objects.
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