Palmprint Texture Analysis Based on Low-Resolution Images for Personal Authentication
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Online Palmprint Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Kernel Fisher Discriminant Analysis for Palmprint Recognition
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
A Novel Approach of Personal Identification Based on Single Knuckleprint Image
APCIP '09 Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02
Personal verification using palmprint and hand geometry biometric
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Finger-knuckle-print: a new biometric identifier
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Efficient person identification by fusion of multiple palmprint representations
ICISP'10 Proceedings of the 4th international conference on Image and signal processing
An introduction to biometric recognition
IEEE Transactions on Circuits and Systems for Video Technology
Phase congruency induced local features for finger-knuckle-print recognition
Pattern Recognition
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Person recognition systems based on biometrics are being increasingly utilized in any applications to enhance the security of physical and logical access systems. A number of biometric traits exist and are in use in various applications. Each biometric trait has its strengths and weaknesses, and the choice depends on the application. Palmprint is one of the relatively new biometrics due to its stable and unique characteristics. The rich texture information of palmprint offers one of the powerful means in person recognition. An important issue in palmprint recognition is to extract features that can discriminate an individual from the other. Recently, a novel hand-based biometric feature, Finger-Knuckle-Print (FKP), has attracted an increasing amount of attention. Like any other biometric identifiers, FKPs are believed to have the critical properties of universality, uniqueness and permanence for person recognition. In this paper, we propose a multiple traits system for person recognition using palmprint and FKP. We have used 1D Log-Gabor response to extract the information from these two traits. So, each trait is represented by the real and the imaginary templates. Such extracted templates are compared with those of the database using the Hamming distance. Using the Hong Kong Polytechnic University (PolyU) database, the experimental results showed that the proposed system achieves excellent performances in terms of computation cost and of recognition rates, for both verification and identification.