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Detection of Unmanned Aerial Vehicles Based on Image Processing

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Telecommunications and Remote Sensing (ICTRS 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1730))

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Abstract

The article proposes and investigates an algorithm for detection on unmanned aerial vehicles (UAV) based on image processing. The algorithm is multi-channel and detects objects at different distances from the camera. It can be used to process both standard video images and thermal images. The advantage of infrared or thermal images is that they can be applied in the bright and dark part of the day, as well as in fog or smoky environments. The results were obtained when processing a real video recording.

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Acknowledgement

This work was supported by the NSP DS program, which has received funding from the Ministry of Education and Science of the Republic of Bulgaria under the grant agreement No Д01-74/19.05.2022.

Author information

Authors and Affiliations

  1. University of Library Studies and Information Technologies, Sofia, Bulgaria

    Ivan Garvanov, Magdalena Garvanova & Daniela Borissova

  2. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Vladimir Ivanov & Daniela Borissova

  3. Nikola Vaptsarov Naval Academy, Varna, Bulgaria

    Andon Lazarov

  4. Prof. Assen Zlatarov University, Burgas, Bulgaria

    Todor Kostadinov

Authors
  1. Ivan Garvanov
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  2. Magdalena Garvanova
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  3. Vladimir Ivanov
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  4. Andon Lazarov
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  5. Daniela Borissova
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  6. Todor Kostadinov
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Corresponding author

Correspondence to Magdalena Garvanova .

Editor information

Editors and Affiliations

  1. Bulgarian Academy of Sciences, Sofia, Bulgaria

    Boris Shishkov

  2. Nikola Vaptsarov Naval Academy, Varna, Bulgaria

    Andon Lazarov

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Garvanov, I., Garvanova, M., Ivanov, V., Lazarov, A., Borissova, D., Kostadinov, T. (2022). Detection of Unmanned Aerial Vehicles Based on Image Processing. In: Shishkov, B., Lazarov, A. (eds) Telecommunications and Remote Sensing. ICTRS 2022. Communications in Computer and Information Science, vol 1730. Springer, Cham. https://doi.org/10.1007/978-3-031-23226-8_3

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  • DOI: https://doi.org/10.1007/978-3-031-23226-8_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23225-1

  • Online ISBN: 978-3-031-23226-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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