Multimodal Biometric System for Identity Verification Based on Hand Geometry and Hand Palm's Veins
Luiz Eduardo de Christo · Annals of Computer Science and Information Systems · 2017
This project was developed with the aim to implement a multibiometric system capable of handling hand palm images acquired using a touchless approach.This considerably increases the difficulty of the image processing task due to the fact that the images from the same person may vary significantly depending on the relative position of the hand regarding the sensor.A modular software tool was developed, providing the user a method for each of these steps: initial image preparation, the feature extraction, processing and fusion, ending with the classification, thus making the researcher's task much easier and faster.The biometric features used for identification include hand geometry features as well as palm vein textures.For the hand geometry data, an algorithm for determining finger tips and hand valleys was proposed and from there was possible to extract a handful of other features related to the geometry of the hand.The handpalm veins' texture features were extracted from a rectangle generated based on the hand's center of mass.The texture descriptor chosen was the Histogram of Gradients.In possession with all the biometric data, the fusion was done on feature level.Support Vector Machine technique was used for the classification.The database chosen for the development of this project was the CASIA Multi-Spectral Palmprint Image Database V1.0.The images used corresponds to the 940nm spectrum due to allowing the visualization of the hand palm's veins.The achieved result for the hand geometry was an EER of 4.77%, for the palm veins an EER of 3.11% and changing the threshold value a FAR of 0.50% and a FRR of 4.82% were achieved.For the fusion of both biometric systems the final result was an EER of 2.33% with a FAR of 1.30% and a FRR of 4.27%.