13-06-2012, 04:10 PM
(09-10-2010, 10:02 AM)projectsofme Wrote:Wavelet Based Palmprint Authentication System
ABSTRACT
Palm print based personal verification has quickly entered the biometric family due to its ease of acquisition, high user acceptance and reliability. This paper proposes a palm print based identification system using the textural information, employing different wavelet transforms. The transforms employed have been analyzed for their individual as well as combined performances at feature level. The wavelets used for the analysis are Biorthogonal, Symlet and Discrete Meyer. The analysis of these wavelets is carried out on 500 images, acquired through indigenously made image acquisition sys-tem. 500 palm print obtained from 50 users with 10 samples each have been collected over a period of six months and have been evaluated for the performance of the proposed system. The experimental results obtained from the data have demon-strated the feasibility of the proposed system by exhibiting Genuine Acceptance Rate, GAR of 97.12%.
INTRODUCTION
Biometrics based personal identification is getting wide acceptance in the networked society, replacing passwords and keys due to its reliability, uniqueness and the ever in-creasing demand of security. Common modalities being used are fingerprint and face but for face authentication people are still working with the problem of pose and illu-mination invariance where as fingerprint does not have a good psychological effect on the user because of its wide use in crime investigations. If any biometric modality is to succeed in the future it should have the traits like unique-ness, accuracy, richness, ease of acquisition, reliability and above all user acceptance. Palm print based personal identi-fication is a new biometric modality which is getting wide acceptance and has all the necessary traits to make it a part of our daily life. This paper investigates the use of palm print for personal identification using combination of dif-ferent wavelets. Palmprint not only has the unique informa-tion available as on the fingerprint but has far more amount of details in terms of principal lines, wrinkles and creases. Moreover it can easily be combined with hand shape bio metric so as to form a highly accurate and reliable biometric based personal identification system. Palmprint based personal verification has become an in-creasingly active research topic over the years. The Palm-print is rich in information and has been analyzed for dis-criminating features like principal lines. The results reported where wavelet transform has been used for feature extraction has motivated us to investigate the effectiveness of using combination of multiple wavelets for the textural analysis of palmprint.
