HomePsychology and Education: A Multidisciplinary Journalvol. 3 no. 10 (2022)

Suspicious Object Detection with Alarm Notification for Security Personnel

Benjamin Cornelio Jr

Discipline: Education

 

Abstract:

This study aimed to develop a “suspicious object detection with alarm notification for security personnel”. The main objective of this study was to track or detect suspicious objects, analyze whether it was abandoned, and send a notification to the security personnel. A prototype methodology was used in the development of the system which employed an image processing methodology to analyze the video captured by the cameras. The image processing applied the background extraction, foreground detection, thresholding algorithm, noise reduction algorithm, tracking and detecting algorithm. The system was evaluated by 10 security personnel and 10 I.T. experts using the ISO 25010 criteria in terms of functional suitability, reliability, performance, efficiency, operability, security, compatibility, maintainability, and portability. The overall result of the evaluation was excellent which implied that the system met the standard criteria in system development.



References:

  1. “Security & Safety Challenges in a Globalized World,” FIRST. [Online]. Available: https://www.firstlinepractitioners.com/course/university-of-london-security-safety-challenges-in-a-globalized-world. [Accessed: 1-March-2020].
  2. Ball State University. Suspicious Object. Available: https://www.bsu.edu/about/administrativeoffices/emergency-preparedness/guidelines/suspicious-object  [Accessed: 1-March-2020].
  3. Best Coursera Courses for Security & Safety Challenges in a Globalized World - Best Coursera Course Finder. [Online]. Available: https://bestcourseracourse.com/coursera-security-safety-globalized-world. [Accessed: 3-March-2020].
  4. Rechenberg and A. Rechenberg, “6 Technological Developments in CCTV
  5. Surveillance Systems,” Rechenberg, 28-May-2019. [Online]. Available: https://www.rechenberg.com.au/6-emerging-trends-cctv-surveillance-systems/. [Accessed: 3-March-2020]
  6. T. A. Scally, “State of the Market: Video Surveillance 2018,” SDM Magazine RSS, 01-Mar-2018. [Online]. Available: https://www.sdmmag.com/articles/94822-state-of-the-market-video-surveillance-2018. [Accessed: 3-March-2020].
  7. S. R. J. Ramson, A. Bashar, J. S. Raj, and Ditzinger (2020). Innovative Data Communication Technologies and Application. Springer International Publishing, 2020.
  8. P. Barter, “On-Street Parking Management,” Federal Ministry for Economic Cooperation and Development, 12-Jan-2020. [Online]. Available: http://transferproject.org/. [Accessed: 09-Mar-2020].
  9. D. M. West and J. R. Allen, “How artificial intelligence is transforming the world,” Brookings, 28-Apr-2020. [Online]. Available: https://www.brookings.edu/research/how-artificial-intelligence-is-transforming-the-world/. [Accessed: 11-March-2020].
  10. “ALARM NOTIFICATION,” Cambridge Dictionary. [Online]. Available: https://dictionary.cambridge.org/dictionary/english/alarm [Accessed: 12-March-2020].
  11. “Camera,” Merriam-Webster. [Online]. Available: https://www.merriam-webster.com/dictionary/camera. [Accessed: 12-March-2020].
  12. Image,” LALI. [Online]. Available: http://www.lali-project.eu/style-example/post-2/5/. [Accessed: 12-March-2020]. [12] Oxford Dictionary.
  13. G. B. Shelly and M. Vermaat, Discovering computers: fundamentals: your interactive guide to the digital world. Boston, MA: Course Technology, 2012.
  14. Jiao, L., Zhang, F., Liu, F., Yang, S., Li, L., Feng, Z., & Qu, R. (2019). A Survey of Deep  Learning-Based Object Detection. IEEE Access, 7, 128837-128868.
  15. The Editors of Encyclopedia Britannica, “Security Alarm,” Encyclopedia Britannica, 17-Aug-2012. [Online]. Available: https://www.britannica.com/technology/security-and-protection-system. [Accessed: 31-March-2020].
  16. “Security Personnel,” Security personnel | legal definition of Security personnel by Law Insider. [Online]. Available: https://www.lawinsider.com/dictionary/security-personnel. [Accessed: 1-April-2020].
  17. D. Clark, “What is a Suspicious Item?: Suspicious Packages,” Engage in Learning, 11-Feb-2020. [Online]. Available: https://www.engageinlearning.com/faq/health-safety/suspicious-packages/what-is-a-suspicious-item/. [Accessed: 3-April-2020].
  18.  “TRACK” Cambridge English Dictionary. [Online]. Available: https://dictionary.cambridge.org/us/dictionary/english/track. [Accessed: 3-April-2020].
  19. “Video Camera,” pcmag.com. [Online]. Available: https://www.pcmag.com/encyclopedia/term/video-camera. [Accessed: 3-April-2020].
  20. W. Wei, Building service-oriented government: lessons, challenges and prospects. Singapore: World Scientific, 2013.
  21.  
  22.  “SECURITY CAMERA: TECHNOLOGY GATE,” SECURITY CAMERA | TECHNOLOGY GATE. [Online]. Available: http://www.technologygate.co.uk/security-camera.php. [Accessed: 5-April-2020].
  23. “Deep Machine Learning AI,” Deep Machine Learning AI. [Online]. Available: http://deepmachinelearningai.com/computer-vision/. [Accessed: 6-April-2020].
  24. Grigorova, K., Malysheva, E., & Bobrovskiy, S. (2017). Application of Data Mining and Process Mining approaches for improving e-Learning Processes. In Информационные технологии и нанотехнологии (ИТНТ-2017) (pp. 1960-1966).
  25. O. Genç “Notes on Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL)...,” Medium, 05-Feb-2019. [Online]. Available: https://towardsdatascience.com/notes-on-artificial-intelligence-ai-machine-learning-ml-and-deep-learning-dl-for-56e51a2071c2?gi=c0968dc5d362. [Accessed: 7-April-2020].
  26. Singh, Krishna Kant & Singh, Akansha. (2010). A Study Of Image Segmentation Algorithms For A Study Of Image Segmentation Algorithms For A Study Of Image Segmentation Algorithms For A Study Of Image Segmentation Algorithms For Different Types Of Images Different Types Of Images Different Types Of Images Different Types Of Images. International Journal of Computer Science Issues. 7.
  27. D.S. Guru, Y.H. Sharath Kumar, S. Manjunath, Textural features in flower classification, Mathematical and Computer Modelling, Volume 54, Issues 3–4, 2011, Pages 1030-1036, ISSN 0895-7177, https://doi.org/10.1016/j.mcm.2010.11.032.
  28. “Image Thresholding¶,” OpenCV. [Online]. Available: https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_thresholding/py_thresholding.html. [Accessed: 11-April-2020].
  29. “Otsu's method ,” Everything Explained Today. [Online]. Available: http://everything.explained.today/Otsu's_method/. [Accessed: 31-March-2020].
  30. Tsai, C. M., & Lee, H. J. (2002). Binarization of color document images via luminance and saturation color features. IEEE Transactions on Image Processing, 11(4), 434-451
  31. Jiao, L., Zhang, F., Liu, F., Yang, S., Li, L., Feng, Z., & Qu, R. (2019). A Survey of Deep Learning-Based Object Detection. IEEE Access, 7, 128837-128868.
  32. D. Adalinge1 and D. Patil, “Survey on Abandoned Object Detection using Image Processing,” International Journal of Innovative Research in Computer and Communication Engineering, vol. 5, no. 5, May 2007.
  33. Danker, A. J., & Rosenfeld, A. (1981). Blob detection by relaxation. IEEE Transactions on Pattern Analysis and Machine Intelligence, (1), 79-92.
  34. Mishra, M. S. K., Jtmcoe, F., & Bhagat, K. S. (2015). A survey on human motion detection and surveillance. International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE) Volume, 4.
  35. Jung, S., Cho, Y., Kim, D., & Chang, M. (2020). Moving object detection from moving camera image sequences using an inertial measurement unit sensor. Applied Sciences, 10(1), 268.
  36. Lavanya, M. P. (2014). Real time motion detection using background subtraction method and frame difference. Int. J. Sci. Res.(IJSR), 3(6), 1857-1861.
  37. Gary Bradski and Adrian Kaehler. Learning OpenCV: Computer vision with the OpenCV library. " O’Reilly Media, Inc.", 2008.
  38. Luna, E., San Miguel, J. C., Ortego, D., & Martínez, J. M. (2018). Abandoned object detection in video-surveillance: survey and comparison. Sensors, 18(12), 4290.
  39. Joshi, T., Aarya, H., & Kumar, P. (2016). Suspicious object detection. In 2016 2nd International Conference on Advances in Computing, Communication, & Automation (ICACCA)(Fall) (pp. 1-6). IEEE.
  40. Paul, M., Haque, S. M., & Chakraborty, S. (2013). Human detection in surveillance videos and its applications-a review. EURASIP Journal on Advances in Signal Processing, 2013(1), 176.
  41. Tripathi, R.K., Jalal, A.S. & Agrawal, S.C. Suspicious human activity recognition: a review. Artif Intell Rev 50, 283–339 (2018). https://doi.org/10.1007/s10462-017-9545-7