Implementation of Video Surveillance System with Motion Detection based on Network Camera Facilities

움직임 감지를 이용한 네트워크 카메라 기반 영상보안 시스템 구현

  • 이규웅 (상지대학교 컴퓨터정보공학부)
  • Received : 2013.12.23
  • Accepted : 2014.02.07
  • Published : 2014.02.28


It is essential to support the image and video analysis technology such as motion detection since the DVR and NVR storage were adopted in the real time visual surveillance system. Especially the network camera would be popular as a video input device. The traditional CCTV that supports analog video data get be replaced by the network camera. In this paper, we present the design and implementation of video surveillance system that provides the real time motion detection by the video storage server. The mobile application also has been implemented in order to provides the retrieval functionality of image analysis results. We develop the video analysis server with open source library OpenCV and implement the daemon process for video input processing and real-time image analysis in our video surveillance system.


Supported by : 상지대학교


  1. Yang, Ming-Jiang, et al. "Cost effective ip camera for video surveillance." Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on. IEEE, 2009.
  2. XU, Ning. A survey of sensor network applications. IEEE Communications Magazine, 2002, 40.8: 102-114.
  3. FOSCAM CGI/SDK Library Manual
  4. MIGLIORE, Davide A.; MATTEUCCI, Matteo; NACCARI, Matteo. A revaluation of frame difference in fast and robust motion detection. In: Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks. ACM, 2006. p. 215-218.
  5. JING, Guo; SIONG, Chng Eng; RAJAN, Deepu. Foreground motion detection by difference-based spatial temporal entropy image. In: TENCON 2004. 2004 IEEE Region 10 Conference. IEEE, 2004. p. 379-382.
  6. CUTLER, Ross; DAVIS, Larry S.. . Robust real-time periodic motion detection, analysis, and applications. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2000, 22.8: 781-796.
  7. Wang, Yiwei, John F. Doherty, and Robert E. Van Dyck. "Moving object tracking in video." the Proceedings of 29th Applied Imagery Pattern Recognition Workshop, pp.95-101, IEEE, 2000.
  8. AmmarAnuar, KhairulMuzzammilSaipullah, NurulAtiqah Ismail, and Soo Yew Guan. "OpenCV Based Real-Time Video Processing Using Android Smartphone." International Journal of Computer Technology and Electronics Engineering (IJCTEE) Vol 1, No. 3, pp58-63, 2011
  9. OpenCV, Open source Computer Vision library. In, 2009.
  10. Zhong-Yong Che, Sangchul Kim, "A Surveillance System Using Images and Movement Detection Sensors" Journal of the Institute of Internet, Broadcasting and Communication, VOL. 13 No. 1, February 2013
  11. Hye-Youn Lim, Dae-Seong Kang, The Moving Object estimation Using an Efficient Background Extraction in the Outdoor Environment, Journal of Korean Institute of Information Technology, Vol 7, No. 3, 2014. 226-231.

Cited by

  1. Vehicle Speed Measurement using SAD Algorithm vol.14, pp.5, 2014,
  2. Fast Human Detection Algorithm for High-Resolution CCTV Camera vol.15, pp.8, 2014,