Journals / Electrica / 2020 / Cilt: 20 - Sayı: 2

Touchless Authentication System Using Visual Fingertip Trajectories

Journal
Electrica
Pages
143–152
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Experimental results show that the proposed system proved its efficiency in various backgrounds where the finger is oriented in various directions.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Biometric traces which are left on the screen of a security device or a mobile phone may cause a threat for the privacy of people when such personal data is likely to be stolen.
📊
Key Findings & Data:The accurate detection of fingertip with invariance to pose, lightning and brightness is essential and crucial for security.
💡
Conclusion & Impact:Experimental results show that the proposed system proved its efficiency in various backgrounds where the finger is oriented in various directions.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Özet

Biometric traces which are left on the screen of a security device or a mobile phone may cause a threat for the privacy of people when such personal data is likely to be stolen. In order to overcome this problem, a touchless authentication system is proposed which allows the usage of fingertip trajectories for creating or entering personal information such as password. First, fingertip regions are detected with Haarcascade method and these regions are tracked using Lucas-Kanade algorithm. The accurate detection of fingertip with invariance to pose, lightning and brightness is essential and crucial for security. Experimental results show that the proposed system proved its efficiency in various backgrounds where the finger is oriented in various directions. Having low computational effort, this system is suitable for low cost and real time processing.

🔖

Cite This Article

AKMAN, V. M., VURAL, R. A., KOÇ, K. T. (2020). Touchless Authentication System Using Visual Fingertip Trajectories. Electrica, Cilt: 20 - Sayı: 2, 143–152. https://ajindex.com/articles/153732

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (14)

  1. P. Viola and M. Jones “Rapid Object Detection using a Boosted Cascade of Simple Features,” IEEE Conf. Computer Vision and Pattern Recognition (CVPR), vol. 1, Dec. 2001
  2. R.M. Gurav, P.K. Kadbe, “Real time Finger Tracking and Contour Detection for Gesture Recognition using OpenCV,” Int. Conf. Industrial Instrumentation and Control (ICIC), pp. 974-977, May 2015
  3. Y. Chunxuan, W. Jingtao, “Finger-Fist Detection in First-Person View based on Monocular Vision using Haar-Like Features” 33rd Chinese Control Conf., pp. 4920-4923, June 2014
  4. Y. Ma, X. Ding, “Robust Real-Time Face Detection Based on Cost-Sensitive AdaBoost Method,” Int. Conf. Multimedia and Expo, ICME’03 Proc., vol. 2, pp. 465-472, 2003
  5. Y. Freund, R.E. Schapire, “A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting,” J. Computer and Systems Sciences, vol. 55, pp. 119-139, 1997
  6. K. Tieu, P. Viola, “Boosting Image Retrieval,” IEEE Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 228-235, 2000
  7. E. ul Haq, S.J.H. Pirzada, M.W. Bing, “New Hand Gesture Recognition Method for Mouse Operations,” IEEE 54th Int. Midwest Symp. Circuits and Systems, pp. 1-4, Aug. 2011
  8. D. Popa, V. Gui, M. Otesteanu, “Real-Time Finger Tracking with Improved Performance in Video Sequences with Motion Blur,” 38th Int. Conf. Telecommunications and Signal Processing (TSP), pp. 1-6, June 2015
  9. R. Agrawal, N. Gupta, “Real Time Hand Gesture Recognition for Computer Interaction,” IEEE 6th Int. Conf. Advanced Computing, pp. 73-77, Feb. 2014
  10. R. Meena Prakash, T. Deepa, T. Gunasundari, N. Kasthuri, “Gesture Recognition and Finger Tip Detection for Human Computer Interaction,” Int. Conf. Innovations in Information, Embedded and Communication Systems, pp. 1-4, March 2017
  11. G. Simion, V. Gui, M. Otesteanu, “Finger Detection Based on Hand Contour and Colour Information,” 6th IEEEInt. Symp. Applied Computational Intelligence and Informatics (SACI), pp. 97-100, May 2011
  12. S.K. Kang, M.Y. Nam, P.K. Rhee, “Color Based Hand and Finger Detection Technology for User Interaction,” Int. Conf. Convergence Hybrid Information Technology, pp. 229-236, 2008
  13. C. Joniez, E. Monari, C. Qui, “Towards Touchless Palm and Finger Detection for Fingerprint Extraction with Mobile Devices,” Int. Conf. Biometrics Special Interest Group, pp. 1-8, Sep. 2015
  14. G. Wu, W. Kang, “Robust Fingertip Detection in a Complex Environment,” IEEE Trans. Multimedia, vol. 18, no. 6, pp. 978-987, Jun