Finger knuckle print authentication has been researched not only as a supplemental authentication modality to fingerprint recognition but also as a method for logging into a PC or entering a building. However, in previous works, some specific devices were necessary to capture a finger knuckle print and users had to keep their fingers perfectly still to capture their finger knuckle. In this paper, we propose a new on the fly finger knuckle print authentication system using a general web camera. In our proposed authentication system, users can input their finger knuckle prints without needing their hand to remain motionless during image capture. We also evaluate the authentication accuracy of the proposed system, achieving an 7% EER under best conditions.
In large-scale biometric authentication systems such as the US-Visit (USA), a 10-fingerprints scanner which simultaneously captures four fingerprints is used. In traditional systems, specific hand-types (left or right) are indicated, but it is difficult to detect hand-type due to the hand rotation and the opening and closing of fingers. In this paper, we evaluated features that were extracted from hand images (which were captured by a general optical scanner) that are considered to be effective for detecting hand-type. Furthermore, we extended the knowledge to real fingerprint images, and evaluated the accuracy with which it detects hand-type. We obtained an accuracy of about 80% with only three fingers (index, middle, ring finger).