Skip to main content

Advertisement

Springer Nature Link
Log in

Real Time Image Encoding for Fast IOT (Internet of Things) Based Video Vigilance System

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

In recent times, technology has played an important role in almost every field as it advances. Law and order situation in the third world countries are extensively poor, and it is imperative to aid the institutions providing security by incorporating systems capable of identifying perpetrators and catch them. It is a well-known fact that security and surveillance industry is evolving, and most of the system are based on video surveillance rather than the basic alarm based solutions. Such systems are integrated with multiple cameras which provide live video surveillance features and in turn increases the visibility of the security systems. The Internet of Things (IOT) is helping to create an efficient security system capable of acquiring live video streams from multiple sensory sources. Due to the lack of available bandwidth, it may not be possible to acquire a video stream with decent quality. In this paper, a compression algorithm is proposed based on discrete cosine transform (DCT) and temporal reduction using motion vectors extracted from the incoming frames in order to achieve best compromise between quality and streaming time to properly indicate the perpetrator. Most of the time, it becomes impossible to seize the perpetrator due to the inferior video quality which makes him unidentifiable. Degraded video quality is mostly due to over compression. Implementation of the proposed algorithm is performed in MATLAB environment by acquiring the live video streams of the videos in real time. Mean Squared Error (MSE) and Peak Signal to Noise Ratio are calculated in order to elaborate the quality difference between the reconstructed frames by conventional means and with the incorporated Temporal Masking technique. By incorporating the proposed algorithm in the compression technique, it was discovered that it actually reduces the stream delay by 0.104 s with an acceptable Structural Similarity Index (SSIM) difference between the reconstructed frames acquired by conventional means and by proposed Temporal Masking Technique.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Çaylı, A., Akyüz, A., Baytorun, A. N., Boyacı, S., Üstün, S., & Kozak, F. B. (2017). Control of greenhouse environmental conditions with IOT based monitoring and analysis system. Turkish Journal of Agriculture-Food Science and Technology, 5(11), 1279–1289.

    Article  Google Scholar 

  2. Gia, T. N., Ali, M., Ben Dhaou, I., Rahmani, A. M., Westerlund, T., Liljeberg, P., et al. (2017). IoT-based continuous glucose monitoring system: A feasibility study. Procedia Computer Science, 11, 327–334.

    Article  Google Scholar 

  3. Xu, B., Xu, L., Cai, H., Jiang, L., Luo, Y., & Gu, Y. (2017). The design of an m-Health monitoring system based on a cloud computing platform. Enterprise Information Systems, 11(1), 17–36.

    Article  Google Scholar 

  4. Li, C., Hu, X., & Zhang, L. (2017). The IoT-based heart disease monitoring system for pervasive healthcare service. Procedia Computer Science, 112, 2328–2334.

    Article  Google Scholar 

  5. Piyare, R. (2013). Internet of things: ubiquitous home control and monitoring system using android based smart phone. International Journal of Internet of Things, 2(1), 5–11.

    Google Scholar 

  6. Tao, M., Zuo, J., Liu, Z., Castiglione, A., & Palmieri, F. (2018). Multi-layer cloud architectural model and ontology-based security service framework for IoT-based smart homes. Future Generation Computer Systems, 78, 1040–1051.

    Article  Google Scholar 

  7. Yang, J., He, S., Lin, Y., & Lv, Z. (2017). Multimedia cloud transmission and storage system based on internet of things. Multimedia Tools and Applications, 76(17), 17735–17750.

    Article  Google Scholar 

  8. Toderici, G., Vincent, D., Johnston, N., Hwang, S. J., Minnen, D.,Shor, J,.& Covell, M. (2017). Full resolution image compression with recurrent neural networks. In CVPR (pp. 5435–5443).

  9. Yee, D., Soltaninejad, S., Hazarika, D., Mbuyi, G., Barnwal, R., & Basu, A., (2017) Medical image compression based on region of interest using better portable graphics (BPG), In 2017 IEEE international conference on systems, man, and cybernetics (SMC) (pp. 216–221). IEEE.

  10. Aldossari, M., Alfalou, A., & Brosseau, C. (2017). Performance evaluation of the multiple-image optical compression and encryption method by increasing the number of target images. In Optics and photonics for information processing XI, Volume 10395. International society for optics and photonics.

  11. Magar, S. S., & Sridharan, B. (2018). Comparative analysis of biomedical image compression using oscillation concept and existing methods. In D. J. Hemanth & S. Smys (Eds.), Computational vision and bio inspired computing (pp. 205–214). Cham: Springer.

    Chapter  Google Scholar 

  12. Gulve, S. P., Khoje, S. A., & Pardeshi, P. (2017). Implementation of IoT-based smart video Surveillance system. In H. S. Behera, J. Nayak, B. Naik, & A. Abraham (Eds.), Computational intelligence in data mining (pp. 771–780). Singapore: Springer.

    Chapter  Google Scholar 

  13. Alsmirat, M. A., Jararweh, Y., Obaidat, I., & Gupta, B. B. (2017). Internet of surveillance: a cloud supported large-scale wireless surveillance system. The Journal of Supercomputing, 73(3), 973–992.

    Article  Google Scholar 

  14. Motlagh, N. H., Bagaa, M., & Taleb, T. (2017). UAV-based IoT platform: A crowd surveillance use case. IEEE Communications Magazine, 55(2), 128–134.

    Article  Google Scholar 

  15. Jackson, R. R. (2017). Automated, remotely-verified alarm system with intrusion and video surveillance and digitial video recording. U.S. Patent No. 9,600,987. March 21, 2017.

  16. Feng, X., et al. (2017). Towards the security of motion detection-based video surveillance on IoT devices. In Proceedings of the on thematic workshops of ACM multimedia 2017. ACM.

  17. Qadri, M. T., Woods J., Tan K. T., & Ghanbari, M. Temporal masking in no reference mode using motion vectors analysis. ICIC Express Letters, 2913–2920.

Download references

Author information

Authors and Affiliations

  1. Department of Telecommunication Engineering, Sir Syed University of Engineering & Technology, Karachi, Pakistan

    Ali Akbar Siddique

  2. Department of Mechatronics and Biomedical Engineering, Air University, Islamabad, Pakistan

    Zia Mohy-Ud-Din

  3. Department of Electronic Engineering, Sir Syed University of Engineering & Technology, Karachi, Pakistan

    M. Tahir Qadri

Authors
  1. Ali Akbar Siddique
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Zia Mohy-Ud-Din
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. M. Tahir Qadri
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Ali Akbar Siddique.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Siddique, A.A., Mohy-Ud-Din, Z. & Qadri, M.T. Real Time Image Encoding for Fast IOT (Internet of Things) Based Video Vigilance System. Wireless Pers Commun 114, 995–1008 (2020). https://doi.org/10.1007/s11277-020-07404-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-020-07404-0

Keywords