A New Hand Based Biometric Modality & An Automated Authentication System

Nirmal Pandey; Om Prakash Verma; Amioy Kumar

Nirmal Pandey Department of Computer Science & Engineering, Delhi Technological University, New Delhi –110042, India
Om Prakash Verma Department of Computer Science & Engineering, Delhi Technological University, New Delhi –110042, India
Amioy Kumar Formerly Guest Faculty (Department of Computer Science & Engineering), Delhi Technological University New Delhi –110042, India

Keywords: Fistprint; biometric modality; smartphone security; automatic authentication system

Abstract

With increased adoption of smartphones, security has become important like never before. Smartphones store confidential information and carry out sensitive financial transactions. Biometric sensors such as fingerprint scanners are built in to smartphones to cater to security concerns. However, due to limited size of smartphone, miniaturised sensors are used to capture the biometric data from the user. Other hand based biometric modalities like hand veins and finger veins need specialised thermal/IR sensors which add to the overall cost of the system. In this paper, we introduce a new hand based biometric modality called Fistprint. Fistprints can be captured using digital camera available in any smartphone. In this work, our contributions are: i) we propose a new non-touch and non-invasive hand based biometric modality called fistprint. Fistprint contains many distinctive elements such as fist shape, fist size, fingers shape and size, knuckles, finger nails, palm crease/wrinkle lines etc. ii) Prepare fistprint DB for the first time. We collected fistprint information of twenty individuals - both males and females aged from 23 years to 45 years of age. Four images of each hand fist (total 160 images) were taken for this purpose. iii) Propose Fistprint Automatic Authentication SysTem (FAAST). iv) Implement FAAST system on Samsung Galaxy smartphone running Android and server side on a windows machine and validate the effectiveness of the proposed modality.

The experimental results show the effectiveness of fistprint as a biometric with GAR of 97.5 % at 1.0% FAR.

Downloads

Download data is not yet available.

References

[1] A. K. Jain, R. Bolle, and S. Pankanti (Eds), “BIOMETRICS: Personal Identification in Networked Society,” Kluwer Academic Publishers, 1999.
[2] A.K. Jain, A. Ross, and S. Prabhakar, “An introduction to biometric recognition,” IEEE Trans. Circuits Syst. Video Technol., vol. 14, no. 1, pp. 4–20, Jan. 2004.
[3] A.K. Jain, L. Hong and R. Bolle, "On-line Fingerprint Verification'', IEEE Transactions on PAMI, Vol. 19, No. 4, pp. 302-314, 1997.
[4] L. Hong, Y. Wan and A.K. Jain, "Fingerprint Image Enhancement: Algorithms and Performance Evaluation", IEEE Transactions on PAMI , Vol. 20, No. 8, pp.777-789, August 1998.
[5] S. Pankanti, S. Prabhakar, and A. K. Jain, "On the Individuality of Fingerprints", IEEE Transactions on PAMI, Vol. 24, No. 8, pp. 1010-1025, 2002.
[6] D. Zhang, W. K. Kong, J. You, and M. Wong, “Online palmprint identification,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 9, pp. 1041–1050, Sep. 2003.
[7] J. You, W. Li, and D. Zhang, "Hierarchical palmprint identification via multiple feature extraction," Pattern Recognition, vol. 35, pp. 847-859, 2002.
[8] A. K. Jain and J. Feng, "Latent Palmprint Matching", IEEE Trans. PAMI vol. 31, no. 6, pp. 1032-1047, June, 2009.
[9] A. K. Jain and N. Duta, "Deformable matching of hand shapes for verification", Proc. IEEE International Conference on Image Processing, October 25-28, Kobe, Japan, 1999.
[10] A.K. Jain, A. Ross and S. Pankanti,"A Prototype Hand Geometry-based Verification System", 2nd Int'l Conference on Audio- and Video-based Biometric Person Authentication (AVBPA), Washington D.C.,
pp. 166-171, March 22-24, 1999.
[11] Chih-Lung Lin, and Kuo-Chin Fan, “Biometric verification using thermal images of palm-dorsa vein patterns”, IEEE transactions on circuits and systems for video technology, Vol. 14, pp. 199-213, 2004.
[12] K. Nandakumar, "Multibiometric Systems : Fusion strategies and Template Security", PhD thesis, Department of Computer Science & Engineering, Michigan State University, East Lansing, USA,
2008.
[13] A. Kumar et al., “Dynamic security management in multi-biometrics,” in Multibiometrics for Human Identification Eds. Cambridge, U.K.: Cambridge Univ. Press, 2010.
[14] L. Hong and A. K. Jain, “Integrating faces and fingerprints for personal identification,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 20, no. 12, pp. 1295–1307, Dec. 1998.
[15] R. Frischholz and U. Dieckmann, “BiolD: A multimodal biometric identification system,” Computer, vol. 33, no. 2, pp. 64–68, Feb. 2000.
[16] J. Fierrez-Aguilar, J. Ortega-Garcia, D. Garcia-Romero, and J. Gonzalez-Rodriguez, “A comparative evaluation of fusion strategies for multimodal biometric verification,” in Proc. 4th Int. Conf. AudioVideo-Based Biometric Person Authentication, J. Kittler and M. Nixon, Eds., 2003, vol. LNCS 2688, pp. 830–837.
[17] A. Kumar, D. C. M. Wong, H. C.Shen1, and A. K. Jain, “Personal verification using palmprint and hand geometry biometric,” in Proc. 4th Int.Conf. Audio- Video-Based Biometric Person Authentication, J. Kittler and M. Nixon, Eds., 2003, vol. LNCS 2668, pp. 668–678.
[18] Arun Ross, Anil Jain, “Information Fusion in Biometrics”, Pattern Recognition Letters, vol. 24 pp. 2115–2125, 2003.
[19] A. K. Jain, K. Nandakumar, and A. Ross, “Score normalization in multimodal biometric systems,” Pattern Recognition., vol. 38, no. 12, pp. 2270–2285, 2005.
[20] Kalyan Veeramachaneni, Lisa Ann Osadciw, and Pramod K. Varshney, “An Adaptive Multimodal Biometric Management Algorithm”, IEEE Trans. On Systems, Man, and Cybernetics—Part C: Applications and Reviews, vol. 35, no. 3, August 2005.
[21] Ajay Kumar, Vivek Kanhangad, and David Zhang, “A New Framework for Adaptive Multimodal Biometrics Management”, IEEE Trans. on Information Forensics and Security, Vol. 5, no. 1, pp. 92-102, March 2010.
[22] Y. Ding, D. Zhuang and K. Wang, “A study of hand vein recognition method,” Proc. IEEE Intl. Conf. Mechatronics & Automation, Niagara Falls, Canada, pp. 2106 – 2110, Jul. 2005.
[23] Ajay Kumar, Yingbo Zhou, “Personal Identification using Finger Knuckle Orientation Features”, Electronics Letters, vol. 45, no. 20, September 2009.