Skip to main content
SpringerLink
Log in

Suspicious Object Search in Airborne Camera Video Stream

  • Conference paper
  • First Online:
Advances in Computer Science for Engineering and Education (ICCSEEA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 754))

Abstract

In some areas of drone application an object search task arises. Also there are cases where usage of standard approaches, e.g. object detection methods or fully manual video view, could be complicated or problematic. However it is possible to find local image (video frame) areas where suspicious object potentially can be present in such cases. We propose (i) an algorithm for suspicious object search in real time and (ii) an automated system (drone and ground control station) based on it, show brief results of its testing, make conclusions about further research direction.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Piccardi, M.: Background subtraction techniques: a review. In: IEEE International Conference on Systems, Man and Cybernetics, pp. 3099–3104. IEEE, The Hague (2004)

    Google Scholar 

  2. Krishna, M.T.G., Ravishankar, M., Babu, D.R.R.: Automatic detection and tracking of moving objects in complex environments for video surveillance applications. In: 2011 3rd International Conference on Electronics Computer Technology, pp. 234–238. IEEE, Kanyakumari (2011)

    Google Scholar 

  3. Mohan, A.S., Resmi, R.: Video image processing for moving object detection and segmentation using background subtraction. In: 2014 First International Conference on Computational Systems and Communications (ICCSC), pp. 288–292. IEEE, Trivandrum (2014)

    Google Scholar 

  4. Risha, K.P., Kumar, A.C.: Novel method of detecting moving object in video. Procedia Technol. 24, 1055–1060 (2016)

    Article  Google Scholar 

  5. Appiah, O., Ben Hayfron-Acquah, J.: A robust median-based background updating algorithm. Int. J. Image Graph. Signal Process. (IJIGSP) 9(2), 1–8 (2017). https://doi.org/10.5815/ijigsp.2017.02.01

    Article  Google Scholar 

  6. Brunelli, R.: Template Matching Techniques in Computer Vision: Theory and Practice. Wiley, Chichester (2009)

    Book  Google Scholar 

  7. Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. PAMI-8(6), 679–698 (1986)

    Article  Google Scholar 

  8. Poobathy, D., Chezian, R.M.: Edge detection operators: peak signal to noise ratio based comparison. Int. J. Image Graph. Signal Process. (IJIGSP) 6(10), 55–61 (2014). https://doi.org/10.5815/ijigsp.2014.10.07

    Article  Google Scholar 

  9. Singh, S., Saurav, S., Shekhar, C., Vohra, A.: Moving object detection scheme for automated video surveillance systems. Int. J. Image Graph. Signal Process. (IJIGSP) 8(7), 49–58 (2016). https://doi.org/10.5815/ijigsp.2016.07.06

    Article  Google Scholar 

  10. Cai, F., Chen, H., Ma, J.: Man-made object detection based on texture clustering and geometric structure feature extracting. Int. J. Inf. Technol. Comput. Sci. (IJITCS) 3(2), 9–16 (2011)

    Google Scholar 

  11. Cai, F., Chen, H., Ma, J.: Man-made object detection based on texture visual perception. Int. J. Eng. Manuf. 2(3), 1–8 (2012)

    Google Scholar 

  12. Papic, V., Turic, H., Dujmic, H.: Two-stage segmentation for detection of suspicious objects in aerial and long-range surveillance applications. In: 10th WSEAS International Conference on Automation & Information, WSEAS, Athens, Greece, pp. 1–5 (2009)

    Google Scholar 

  13. Prystavka, P., Rogatyuk, A.: The mathematical foundations of foreign object recognition in the video from unmanned aircraft. Proc. Natl. Aviat. Univ. 3(64), 133–139 (2015)

    Google Scholar 

  14. Chyrkov, A.: Suspicious object search on video stream from unmanned aircraft camera by using histogram analysis. Probl. Creat. Test. Appl. Oper. Complex Inf. Syst. 13, 126–135 (2016). (in Ukrainian)

    Google Scholar 

  15. Kasyanov, Y.: – YouTube. https://www.youtube.com/channel/UCTG6kc99C4U6GNEx7h_apwA

  16. Prystavka, P., Sorokopud, V., Chyrkov, A.: Experimental version of an automated system for suspicious object search on video stream from unmanned aircraft. Weapon Syst. Military Equip. 2(50), 26–32 (2017). (in Ukrainian)

    Google Scholar 

  17. Nichikov, E., Chyrkov, A.: Information technology of unmanned aircraft camera field of view definition. Probl. Inf. Control 4(52), 106–112 (2015). (in Ukrainian)

    Google Scholar 

  18. Buryi, P., Pristavka, P., Sushko, V.: Automatic definition the field of view of camera of unmanned aerial vehicle. Sci.-Based Technol. 2(30), 151–155 (2016)

    Google Scholar 

  19. Piskunov, O., Yurchuk, I., Bilyanska, L.: Camera field of view definition for aerial photography. Sci.-Based Technol. 3(35), 204–208 (2017). (in Ukrainian)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National Aviation University, Kosmonavt Komarov ave., 1, Kyiv, Ukraine

    Artem Chyrkov & Pylyp Prystavka

Authors
  1. Artem Chyrkov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pylyp Prystavka
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Artem Chyrkov .

Editor information

Editors and Affiliations

  1. School of Educational Information Technology, Central China Normal University, Wuhan, Hubei, China

    Zhengbing Hu

  2. Mechanical Engineering Research Institute, Russian Academy of Sciences, Moscow, Russia

    Sergey Petoukhov

  3. Faculty of Applied Mathematics, National Technical University of Ukraine “Igor Sikorsky Kiev Polytechnic Institute”, Kiev, Ukraine

    Ivan Dychka

  4. Halmos College of Natural Sciences and Oceanography, Nova Southeastern University, Ft. Lauderdale, Florida, USA

    Matthew He

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Chyrkov, A., Prystavka, P. (2019). Suspicious Object Search in Airborne Camera Video Stream. In: Hu, Z., Petoukhov, S., Dychka, I., He, M. (eds) Advances in Computer Science for Engineering and Education. ICCSEEA 2018. Advances in Intelligent Systems and Computing, vol 754. Springer, Cham. https://doi.org/10.1007/978-3-319-91008-6_34

Download citation

Publish with us

Policies and ethics

Search

Navigation