Personal Authentication Using Hand Vein Triangulation and Knuckle Shape

• Published in: IEEE transactions on image processing Vol. 18; no. 9; pp. 2127 - 2136
• Main Authors: Kumar, A., Prathyusha, K.V.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.09.2009; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Authentication; Biometrics; Biometry - methods; Contact free hand recognition; Cryptography; Data mining; Detection, estimation, filtering, equalization, prediction; Error analysis; Exact sciences and technology; Extraction; Finger Joint - anatomy & histology; Hand - anatomy & histology; Hand - blood supply; hand shape; hand vein; Humans; Image processing; Image Processing, Computer-Assisted - methods; Information theory; Information, signal and communications theory; Infrared; Infrared imaging; Infrared Rays; Matching; Models, Statistical; Optical imaging; Palm; palm dorsal vein; Pattern Recognition, Automated; ROC Curve; Security Measures; Shape; Signal and communications theory; Signal processing; Signal, noise; Telecommunications and information theory; Topology; Triangulation; vascular biometrics; Veins; Veins - anatomy & histology; Biometrics; Multistage method; Triangulation; hand shape; Error rate; Information extraction; Identification; Pattern recognition; Joint; hand vein; Near infrared radiation; Interest region; Authentication; Contact free hand recognition; Palm; Information processing; vascular biometrics; Thermal imaging; palm dorsal vein; Automatic recognition; Cost lowering
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2009.2023153

This paper presents a new approach to authenticate individuals using triangulation of hand vein images and simultaneous extraction of knuckle shape information. The proposed method is fully automated and employs palm dorsal hand vein images acquired from the low-cost, near infrared, contactless imaging. The knuckle tips are used as key points for the image normalization and extraction of region of interest. The matching scores are generated in two parallel stages: (i) hierarchical matching score from the four topologies of triangulation in the binarized vein structures and (ii) from the geometrical features consisting of knuckle point perimeter distances in the acquired images. The weighted score level combination from these two matching scores are used to authenticate the individuals. The achieved experimental results from the proposed system using contactless palm dorsal-hand vein images are promising (equal error rate of 1.14%) and suggest more user friendly alternative for user identification.