Multimodal Biometric Recognition Based on 3D Ultrasound Palmprint-Hand Geometry Fusion

In recent years, multimodal biometric systems are increasingly employed in many application field due to several advantages in terms of universality, recognition rate. and security. Among various acquisition technologies, Ultrasound shows important merits, because it allows obtaining volumetric images of the human body and hence a more accurate description of characteristics and to verify liveness. In this work, a multimodal ultrasound recognition system based on the fusion between 3D hand geometry and 3D palmprint features is proposed and experimentally evaluated. The system acquires a volumetric image of the whole hand and for both characteristics, several 2D images are extracted at different depth levels. From each image, 2D features are extracted and then properly combined to achieve a 3D template. Recognition performances are evaluated through verification and identification experiments by employing a homemade database. Experiments are carried out first for the two unimodal biometrics and successively, by fusing the two modalities at score level. Results have shown that fusion is able to dramatically improve the recognition performances of the single biometrics, achieving an Equal Error Rate of 0.08% and an identification rate of 100%.