Detecting Finger-Vein Presentation Attacks Using 3D Shape & Diffuse Reflectance Decomposition

Despite the high biometric performance, finger-vein recognition systems are vulnerable to presentation attacks (aka., spoofing attacks). In this paper, we present a new and robust approach for detecting presentation attacks on finger-vein biometric systems exploiting the 3D Shape (normal-map) and material properties (diffuse-map) of the finger. Observing the normal-map and diffuse-map exhibiting enhanced textural differences in comparison with the original finger-vein image, especially in the presence of varying illumination intensity, we propose to employ textural feature-descriptors on both of them independently. The features are subsequently used to compute a separating hyper-plane using Support Vector Machine (SVM) classifiers for the features computed from normal-maps and diffuse-maps independently. Given the scores from each classifier for normal-map and diffuse-map, we propose sum-rule based score level fusion to make detection of such presentation attack more robust. To this end, we construct a new database of finger-vein images acquired using a custom capture device with three inbuilt illuminations and validate the applicability of the proposed approach. The newly collected database consists of 936 images, which corresponds to 468 bona fide images and 468 artefact images. We establish the superiority of the proposed approach by benchmarking it with classical textural feature-descriptor applied directly on finger-vein images. The proposed approach outperforms the classical approaches by providing the Attack Presentation Classification Error Rate (APCER) & Bona fide Presentation Classification Error Rate (BPCER) of 0% compared to comparable traditional methods.

1. Introduction

The use of finger-vein as a type of a biometric characteristic for verification is growing in recent years, especially for banking transaction applications, where there is a need for highly secure access control [9]. The practical example of such systems can be found in commercial applications that were developed by Hitachi in 2004 with finger-vein verification mainly for use in unsupervised scenarios such as Bank ATMs [9]. Despite the high recognition accuracy of such finger-vein systems, they are prone to attacks at the capture level where one can use an artefact (e.g., printed finger-vein image) to gain illegitimate access, especially in unsupervised access control settings. Such attacks at the capture level are popularly termed as presentation attacks (aka., spoofing attacks), and attacks can be carried out using different kind of artefacts, such as using a printed photo of a finger-vein representation (print-attack) or alternatively using an electronic display to show the vein representation (display-attack)[24].