Abstract
Similar to biometric fingerprint recognition, characteristic minutiae points – here end and branch points – can be extracted from skeletonised vein images to distinguish individuals. An approach to extract those vein minutiae and to transform them into a fixed-length, translation and scale invariant representation where rotations can be easily compensated is presented in this study. The proposed solution based on spectral minutiae is evaluated against other comparison strategies on three different datasets of wrist and palm dorsal vein samples. The authors' analysis shows a competitive biometric performance while producing features that are compatible with state-of-the-art template protection systems. In addition, a modified and more distinctive, but not transform or rotation invariant, representation is proposed and evaluated.
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