Biometric Identification through Hand Geometry Measurements
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hand Recognition Using Implicit Polynomials and Geometric Features
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Personal verification using palmprint and hand geometry biometric
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
An introduction to biometric recognition
IEEE Transactions on Circuits and Systems for Video Technology
Classifier Ensemble Generation for the Majority Vote Rule
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Hi-index | 0.00 |
A new approach for personal identification using hand geometry based upon geometrical and shape features is presented. We propose a new pegless hand geometry verification system where the users are free to put their hand in arbitrary fashion. A Linear Discirminant Analysis if applied to the raw data in order to perform a best clustering of the feature space. The combination of three different neural network classifiers (unsupervised SOM, supervised SOM and LVQ) gives 0.35% FAR and 0.15% FRR. The method has been tested on a large size database of 1400 images for training and 1400 for test from 280 individuals suitable for medium and low security applications.