An Efficient Secure Multimodal Biometric Fusion Using Palmprint and Face Image

IJCSI International Journal of Computer Science Issues, Vol. 2, 2009 52

Fig.2. Canonical form based Palm images.

(a) Original image (b) Grey image (c) Resized image (d) Normalized
modal image (e) Diagonalization image

Fig.3. Canonical form based Face images.

(a) Original image (b) Grey image (c) Resized image

(d) Normalized modal image (e) Diagonalization image

The multimodal system has been designed at multi-
classifier & multimodal level. At multi-classifier level,
multiple algorithms are combined better results. At first
experimental the individual systems were developed and
tested for FAR, FRR & accuracy. Table1 shows FAR,
FRR & Accuracy of the systems.

In the last experiment both the traits are combined at
matching score level using sum of score technique. The
results are found to be very encouraging and promoting
for the research in this field. The overall accuracy of the
system is more than 97%, FAR & FRR of 2.4% & 0.8%
respectively.

6 Conclusion

Biometric systems are widely used to overcome the
traditional methods of authentication. But the unimodal
biometric system fails in case of biometric data for
particular trait. Thus the individual score of two traits
(face & palmprint) are combined at classifier level and
trait level to develop a multimodal biometric system. The
performance table shows that multimodal system performs
better as compared to unimodal biometrics with accuracy
of more than 98%.

References

[1] Ross.A.A, Nandakumar.K, Jain.A.K. Handbook of Multibiometrics.
Springer-Verlag, 2006.

[2] Kumar.A, Zhang.D Integrating palmprint with face for user
authentication. InProc.Multi Modal User Authentication Workshop,
pages 107-112, 2003.

[3] Feng.G, Dong.K, Hu.D, Zhang.D When Faces Are Combined with
Palmprints: A Novel Biometric Fusion Strategy. In Proceedings of
ICBA, pages 701-707, 2004.

[4] G. Feng, K. Dong, D. Hu & D. Zhang, when Faces are combined with
Palmprints: A Noval Biometric Fusion Strategy, ICBA, pp.701-707,
2004.

[5] M. Turk and A. Pentland, “Face Recognition using Eigenfaces”, in
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591-1991.

[6] M. Turk and A. Pentland, “Face Recognition using Eigenfaces”,
Journals of Cognitive Neuroscience, March 1991.

[7] L. Sirovitch and M. Kirby, “Low-dimensional Procedure for the
Characterization of Human Faces”, Journals of the Optical Society of
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[8] Kirby.M, Sirovitch.L. “Application of the Karhunen-Loeve Procedure
for the Characterization of Human Faces”, IEEE Transaction on
Pattern Analysis and Machine Intelligence, vol. 12, pp. 103-108,
January 1990.

[9] Daugman.J.G, “High Confidence Visual Recognition of Persons by a
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Nageshkumar M., graduated in Electronics and

IJCSI

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