Anti-theft Motorcycle System Using Face Recognition by Deep Learning Under Concept on Internet of Things

  • Apichat SilsanpisutEmail author
  • Patcharaon Petchsamutr
  • Mahasak Ketcham
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 807)


The special problem aimed at to develop an anti-theft motorcycle system using face recognition by deep learning under concept on internet of things for use in the prevention of theft motorcycle. The special problem is used this technique face detection, face recognition and internet of things by measuring the image received from the camera to compare the original owners of the motorcycle when it detects that the original image and the image received from the camera that does not match.

The results of system are equipment and incoming image from the camera accurately for increase the effectiveness of the theft motorcycle and the system can used in current.


Motorcycle Face recognition Deep learning Internet of Things 


  1. 1.
    Motorcycle registration statistics, Department of Land Transport.
  2. 2.
    Robbery, Office of the Royal Society.โจรกรรม-๕-เมษายน-๑๕๕๓Google Scholar
  3. 3.
    Statistics motorcycle theft, Little Lee.
  4. 4.
    Guo, H., et al.: An automotive security system for anti-theft (2009)Google Scholar
  5. 5.
    Hameed, S.A., et al.: Car monitoring alerting and tracking model (2010)Google Scholar
  6. 6.
    Sirisak, L.: The Format of the Memory Card by Using Image Processing and Neural Network. Master of Engineering Thesis Major McKee electronic, Suranaree University of Technology, Thailand (2012)Google Scholar
  7. 7.
    Bagavathy, P., et al.: Real Time Car Theft Decline System Using arm Processor (2011)Google Scholar
  8. 8.
    Liu, Z., et al.: Vehicle Anti-theft Tracking System Based on Internet of Things (2013)Google Scholar
  9. 9.
    Amos, B., Ludwiczuk, B., Satyanarayanan, M.: OpenFace: a generalpurpose face recognition library with mobile applications, June 2016. CMU-CS-16-118Google Scholar
  10. 10.
    Bagavathy, P., Dhaya, R., Devakumar, T.: Real time car theft decline system using ARM processor. In: 3rd International Conference on Advances in Recent Technologies in Communication and Computing (ARTCom 2011) (2011)Google Scholar
  11. 11.
    Liu, S.-S., Tian, Y.-T., Li, D.: New research advances of facial expression recognition. In: 2009 International Conference on Machine Learning and Cybernetics, vol. 2, pp. 1150–1155 (2009)Google Scholar
  12. 12.
    Zhao, W., Chellappa, R., Phillips, P.J., Rosenfeld, A.: Face recognition: a literature survey. ACM Comput. Surv. 35, 399–458 (2003)CrossRefGoogle Scholar
  13. 13.
    Lee, C., Landgrebe, D.: Feature Extraction and Classification Algorithms for High Dimensional Data. Purdue University (1993)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Apichat Silsanpisut
    • 1
    Email author
  • Patcharaon Petchsamutr
    • 1
  • Mahasak Ketcham
    • 1
  1. 1.Faculty of Information TechnologyKing Mongkut’s University of Technology North BangkokBangkokThailand

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