Multispectral palmprint identification by Hybrid Haar Wavelet employing multiple score level fusion modus operandi

The Hybrid Haar Wavelet proposed in this paper is simple to generate and exhibit an excellent value of EER as system implementation. The Hybrid Haar Wavelet is generated by reiterated kronecker product of basis haar wavelet with itself. This paper describes a new method to authenticate individuals based on their palmprint identification. ROC plot of FMR v/s FNMR is generated based on the values obtained by score level fusion of red, blue, and green palm scans. The Hybrid Haar Wavelet proposed in this paper provides for a fool-proof system with GAR of 91.2% at a threshold of 7. One-to-many identification of 6000 multi-spectral palmprint images from 500 different palms is used to validate the performance of the system, with 14 fusion schemes proposed to increase GAR while reducing FMR of the system. Minimum EER obtained is 2%, with a maximum GAR of 100%. The system being fool-proof can be efficiently implemented for high security applications like military access.

[1]  H. B. Kekre,et al.  Identification of multi-spectral palmprints using energy compaction by Hybrid wavelet , 2012, 2012 5th IAPR International Conference on Biometrics (ICB).

[2]  Anil K. Jain Fundamentals of Digital Image Processing , 2018, Control of Color Imaging Systems.

[3]  Rekha Vig,et al.  Automated Fingerprint Identification System based on Sectorized Complex Walsh Plane , 2011 .

[4]  Pillem Ramesh,et al.  New Palm Print Authentication System by Using Wavelet Based Method , 2011 .

[5]  E. Jacobsen,et al.  The sliding DFT , 2003, IEEE Signal Process. Mag..

[6]  Nikola Paveši,et al.  Personal authentication using hand-geometry and palmprint features – the state of the art , 2004 .

[7]  Ajay Kumar,et al.  Integrating palmprint with face for user authentication , 2003 .

[8]  Tsuhan Chen,et al.  Biometrics : Challenges arising from Theory to Practice , 2004 .

[9]  Zhenhua Guo,et al.  An Online System of Multispectral Palmprint Verification , 2010, IEEE Transactions on Instrumentation and Measurement.

[10]  Helen C. Shen,et al.  Personal Identification and Verification: Fusion of Palmprint Representations , 2004, ICBA.

[11]  Zhenhua Guo,et al.  Palmprint Verification using Complex Wavelet Transform , 2007, 2007 IEEE International Conference on Image Processing.

[12]  Carmen Sanchez-Avila,et al.  Iris-based biometric recognition using dyadic wavelet transform , 2002 .

[13]  David Zhang,et al.  A survey of palmprint recognition , 2009, Pattern Recognit..

[14]  Charles K. Chui,et al.  An Introduction to Wavelets , 1992 .

[15]  David Zhang,et al.  Personal authentication using multiple palmprint representation , 2005, Pattern Recognit..

[16]  H. B. Kekre,et al.  Palmprint Identification Using Kronecker Product of DCT and Walsh Transforms for Multi-Spectral Images , 2011, 2011 International Conference on Hand-Based Biometrics.

[17]  Helen C. Shen,et al.  Personal Verification Using Palmprint and Hand Geometry Biometric , 2003, AVBPA.

[18]  David Zhang,et al.  Palmprint Identification by Fourier Transform , 2002, Int. J. Pattern Recognit. Artif. Intell..

[19]  Ioannis Pitas,et al.  Digital Image Processing Algorithms and Applications , 2000 .