Intelligent Video Surveillance Systems for Vehicle Identification Based on Multinet Architecture Articles uri icon

publication date

  • July 2022

start page

  • 1

end page

  • 26


  • 7, 325


  • 13

International Standard Serial Number (ISSN)

  • 2078-2489


  • Security cameras have been proven to be particularly useful in preventing and combating crime through identification tasks. Here, two areas can be mainly distinguished: person and vehicle identification. Automatic license plate readers are the most widely used tool for vehicle identification. Although these systems are very effective, they are not reliable enough in certain circumstances. For example, due to traffic jams, vehicle position or weather conditions, the sensors cannot capture an image of the entire license plate. However, there is still a lot of additional information in the image which may also be of interest, and that needs to be analysed quickly and accurately. The correct use of the processing mechanisms can significantly reduce analysis time, increasing the efficiency of video cameras significantly. To solve this problem, we have designed a solution based on two technologies: license plate recognition and vehicle re-identification. For its development and testing, we have also created several datasets recreating a real environment. In addition, during this article, it is also possible to read about some of the main artificial intelligence techniques for these technologies, as they have served as the starting point for this research.


  • Robotics and Industrial Informatics


  • alpr; deep learning algorithms; real-time applications; surveillance systems; vehicle re-identification