A Multimodal Biometric Recognition System based on Fusion of Palmprint and Fingerprint

A Multimodal Biometric Recognition System based on Fusion of Palmprint and Fingerprint

  ijett-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2013 by IJETT Journal
Volume-4 Issue-5                      
Year of Publication : 2013
Authors : Mitul D Dhameliya , Jitendra P Chaudhari

Citation 

Mitul D Dhameliya , Jitendra P Chaudhari. "A Multimodal Biometric Recognition System based on Fusion of Palmprint and Fingerprint". International Journal of Engineering Trends and Technology (IJETT). V4(5):1908-1911 May 2013. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group.

Abstract

Basic aim of a biometric system is automatically discriminate between subjects as well as protect data. It also protects resources access from unauthorized users. We develop a biometric identification system that represents a valid alternative to conventional approaches. In biometric system physical or behavioral traits are used. A multimodal biometri c identification system aims to fuse two or more physical or behavioral traits. Multimodal biometric system is used in order to improve the accuracy. Multimodal biometric identification system based on palmprint& fingerprint trait is proposed. Typically in a multimodal biometric system each biometric trait processes its information independently. The processed information is combined using an appropriate fusion scheme. Successively, the comparison of data base template and the input data is done with the he lp of Euclidean - distance matching algorithm. If the templates are matched we can allow the person to access the system. The experimental results demonstrated that the proposed multimodal biometric system achieves a recognition accuracy of 87% Multimodal bi ometric system provides optimal False Acceptance Rate (FAR) & False Rejection Rate (FRR), thus improving system accuracy & reliability.

References

[1] Jain, A.[Anil] K.; Flynn, Patrick Joseph; Ross, Arun Abraham (2008). Handbook of Biometrics; Springer.
[2] Zhang, D. [David] (2004). Palmprint Authentication; Norwell; mass. Kluwer Academic publishers .
[3] Wu, X; Wang, K; Zhang, D (2004). A novel approach of palm - line extraction; in: Proceeding of the Third International Conference on Image and Graphics .
[4] Han; Chin Chu an; Cheng; HsuLiang; Lin; ChihLung; Fan; Kuo Chin (2003). Personal authentication using palm - print features ; Pattern Recognition (36); No. 2 .
[5] Huang, D.S. [De - Shuang]; Jia, W. [Wei]; Zhang, D.[David] (2008). Palmprint verification based on principal lines; Pattern Recognition (41); No. 4
[6] Prasad, S.M.; Govindan, V.K.; Sathidevi, P .S (2009). Palmprint Authentication Using Fusion of Wavelet Based Representations; 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC2009); 978 - 1 - 4244 - 5612.
[7] Li, W; Zhang, D; Xu, Z (2002). Palmprint identification by Fourier transform ; International Journal of Pattern Recognition and Artificial Intelligence 16 (4) 417 – 432.
[8] Li, Y; Wang, K; Zhang, D (2005). Palmprint recognition based on translation invariant Zernike moments and modular neural network; in: Lecture Notes in Computer Science ; Springer; vol. 3497; pp. 177 – 182.
[9] Kong, K; Zhang, D (2002). Palmprint texture analysis based on low - resolution images for Personal authentication ; in: Proceedings of 16th International Conference on Pattern Recognition ; vol. 3; pp. 8 07 – 810.
[10] J.Daugrnan. Uncertainty relation for resolution in space spatial frequency and orientation Optimized by two dimensional visual cortical filters . Journal of the Optical Society of America A.2:1160 - 1169 ? 1985.
[11] J. Wu, Z.H. Zhou, “Face recognition with one training image per person”. Pattern Recognition. Letter , vol. 23 (14), pp. 1711 – 1719, 2002.
[12] Y. Yao, X. Jing, H. Wong. “Face and palmprint feature level fusion for single sample biometrics recognition” . Neurocomputing , vol. 7 0(7 - 9), pp. 1582 - 1586, March 07.
[13] A. Ross, R. Govindarajan. “Feature - level Fusion using Hand and Face Biometrics”.
[14] Namuduri, K.R.; Mehrotra, R.; Ranganathan, N.(1994). Efficient Co mputation of Gabor Filter Base Multiresolution Responses; PR(27); No. 7; pp. 925 - 938

Keywords
Biometrics, False Acceptance Rate (FAR), False Rejection Rate(FRR) ,KNN , Palmprint Fingerprint trait, Fu sion technique, Identification system, Multimodal.