Publication Type:

Journal Article


Advances in Intelligent Systems and Computing, Springer Verlag, Volume 517, p.539-545 (2017)





Artificial intelligence, Authentication, Biometric authentication system, Biometrics, Computing technology, Cryptography, Digital storage, Encryption algorithms, Evolutionary algorithms, extraction, Image acquisition, Image processing, Image segmentation, infrared radiation, Multi-modal, Multi-modal biometrics, Personal authentication, Region of interest, Unimodal


The modern computing technology has a huge dependence on biometrics to ensure strong personal authentication. The mode of this work is to increase accuracy with less data storage and providing high security authentication system using multimodal biometrics. The proposed biometric system uses two modalities, palm print and palm vein. The preprocessing steps begin with image acquisition of palm print and palm vein images using visible and infrared radiations, respectively. From the acquired image, region of interest (ROI) is extracted. The extracted information is encrypted using encryption algorithms. By this method of encryption, after ROI extraction, the storage of data consumes less memory and also provides faster access to the information. The encrypted data of both modalities are fused using advanced biohashing algorithm. At the verification stage, the image acquired is subjected to ROI extraction, encryption and biohashing procedures. The biohash code is matched with the information in database using matching algorithms, providing fast and accurate output. This approach will be feasible and very effective in biometric field.


cited By ; Conference of International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems, ICAIECES 2016 ; Conference Date: 19 May 2016 Through 21 May 2016; Conference Code:195169

Cite this Research Publication

A. J. Siddharth, Prabha, A. P. Hari, Srinivasan, T. J., and N. Lalithamani, “Palm Print and Palm Vein Biometric Authentication System”, Advances in Intelligent Systems and Computing, vol. 517, pp. 539-545, 2017.