Smart Surveillance using PDA
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32799
Smart Surveillance using PDA

Authors: Basem Mustafa Abd. Amer , Syed Abdul Rahman Al-Attas

Abstract:

The aim of this research is to develop a fast and reliable surveillance system based on a personal digital assistant (PDA) device. This is to extend the capability of the device to detect moving objects which is already available in personal computers. Secondly, to compare the performance between Background subtraction (BS) and Temporal Frame Differencing (TFD) techniques for PDA platform as to which is more suitable. In order to reduce noise and to prepare frames for the moving object detection part, each frame is first converted to a gray-scale representation and then smoothed using a Gaussian low pass filter. Two moving object detection schemes i.e., BS and TFD have been analyzed. The background frame is updated by using Infinite Impulse Response (IIR) filter so that the background frame is adapted to the varying illuminate conditions and geometry settings. In order to reduce the effect of noise pixels resulting from frame differencing morphological filters erosion and dilation are applied. In this research, it has been found that TFD technique is more suitable for motion detection purpose than the BS in term of speed. On average TFD is approximately 170 ms faster than the BS technique

Keywords: Surveillance, PDA, Motion Detection, ImageProcessing , Background Subtraction.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1082259

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1714

References:


[1] Z. Luo and C.H. Wu, "A Chinese Character Recognition Interface for Mobile Communication Devices Using Fuzzy Logic and Unit Extraction", Proceedings of the IEEE IECON 22nd International Conference on Industrial Electronics, Control, and Instrumentation, August 1996. 572-577
[2] H. Kang and H.J. Kim, "Design of an Interface on PDA for Korean", IEEE Transactions on Consumer Electronics, Vol.46, Issue: 3, pp.834- 838, August 2000.
[3] Yu-Fei Ma, Hong-Jiang Zhang. Detecting Motion Object By Spatio- Temporal Entropy Microsoft Research, China 5F, Sigma Center, 49 Zhi Chun Road Beijing, China.
[4] J. Breitbart, D. Balakrishnan, and A. Ganz, "Pocket-IMPACT Software for Delivering Online Courseware on a PDA: Challenges, Design Guidelines and Implementation", Proceedings of IEEE Frontiers in Education Conference, Vol.1, pp. T3F-5, November 2002.
[5] X. Vila, A. Riera, E. Sanchez, M. Lama, D. L. Mureno, "A PDA-based Interface for a Computer Supported Educational System", Proceedings of the 3rd IEEE International Conference on Advanced Learning Technologies, pp.12-16, July 2003.
[6] J. Yang, X. Chen, and W. Kunz, "A PDA-based Face Recognition System", Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision, pp. 19-23, December 2002.
[7] Sheng-Tun Li, Huang-Chih Hsieh, Ly-Yen Shue, Wen-Shen Chen "PDA Watch for Mobile Surveillance Services". Department of Information Management National Kaohsiung First University of Science Technology 2 Juoyue Rd., Nantz District, Kaohsiung 811, Taiwan.
[8] Gregory A. Baxes. 1996. |Digital Image Processing: Principles and Applications. New York: John willey & Sons.
[9] A. J. Lipton, H. Fujiyoshi, and R.S. Patil. Moving target classification and tracking from real-time video. In Proc. of Workshop Applications of Computer Vision, pages 129-136, 1998.
[10] Jeff Prosise. Programming Windows with MFC. Redmond, Washington: Microsoft Press. 1999.
[11] Richardh.Carverkuo Chungtai. Modern Multithreading. Hoboken, New Jersey .John Wiley & Sons. 2006.