Call for Paper - October 2019 Edition
IJCA solicits original research papers for the October 2019 Edition. Last date of manuscript submission is September 20, 2019. Read More

Embedded Car Security System on Face Detection

Print
PDF
2nd National Conference on Information and Communication Technology
© 2011 by IJCA Journal
Number 1 - Article 3
Year of Publication: 2011
Authors:
Vikram Kulkarni
K. Laxmi Narshima Rao

Vikram Kulkarni and Laxmi Narshima K Rao. Article: Embedded Car Security System on Face Detection. IJCA Proceedings on 2nd National Conference on Information and Communication Technology NCICT(3):, November 2011. Full text available. BibTeX

@article{key:article,
	author = {Vikram Kulkarni and K. Laxmi Narshima Rao},
	title = {Article: Embedded Car Security System on Face Detection},
	journal = {IJCA Proceedings on 2nd National Conference on Information and Communication Technology},
	year = {2011},
	volume = {NCICT},
	number = {3},
	pages = {},
	month = {November},
	note = {Full text available}
}

Abstract

In this proposed embedded car security system, FDS (Face Detection System) is used to detect the face of the driver and compare it with the predefined face. For example, in the night when the car s owner is sleeping and someone theft the car then FDS obtains images by one tiny web camera which can be hidden easily in somewhere in the car. FDS compares the obtained image with the predefined images if the image doesn t match, then the information is sent to the owner through MMS. So now owner can obtain the image of the thief in his mobile as well as he can trace the location through GPS. The location of the car as well as its speed can be displayed to the owner through SMS. So by using this system, owner can identify the thief image as well as the location of the car This system prototype is built on the base of one embedded platform in which one SoC named SEP4020 (works at 100MHz) controls all the processes. Experimental results illuminate the validity of this car security system.

Reference

  • S. Ajaz, M. Asim, M. Ozair, M. Ahmed, M. Siddiqui, Z. Mushtaq, “Autonomous Vehicle Monitoring & Tracking System,” SCONEST2005, pp. 1 – 4, 2005.
  • Joseph A. O'Sullivan, Robert Pless, Advances in Security Technologies: Imaging, Anomaly Detection, and Target and Biometric Recognition”, Microwave Symposium IEEE/MTT-S International Volume, Page(s):761 – 764, 2007.
  • Viola P, Jones M, “Rapid Object Detection using a Boosted Cascade of Simple Features” Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, p511, 2001.
  • Lienhart R, Kuranov A, Pisarevsky, “Empirical analysis of detection cascades of boosted classifiers for rapid object detection” Technical report, MRL, Intel Labs, 2002.
  • Viola P, Jones M, “Fast and robust classification using asymmetric AdaBoost and a detector cascade” NIPS 14, 2002.
  • Goldberg D.E, “Genetic algorithms in search, optimization, and machine learning” Addison-Wesley, 1989.
  • Xusheng Tang, Zongying Ou, Tieming Su, Pengfei Zhao, “CascadeAdaBoost Classifiers with Stage Features Optimization for Cellular Phone Embedded Face Detection System” Advances in Natural Computation, p. 688, 2005.
  • Jianxin Wu, M. D. Mullin, J. M. Rehg, “Linear Asymmetric classifier for cascade detectors”, Conf Machine Learning, 2005.
  • PU Han-lai, LING Ming, “Performance Oriented Customization of On-Chip Memory Capacity” Journal of Applied Sciences, p. 364, 2005.
  • Zhang Yu, “Research on High Level Model and Performance Estimation” Southeast University PHD thesis, 2007.
  • ARM Co., “ARM Developer Suite User’s guide” 2001.
  • BioID Face Database.