Feature extraction from vein images using spatial information and chain codes

Abstract

The pattern formed by subcutaneous blood vessels is unique attribute of each individual and can therefore be used as a biometric characteristic. Exploiting the specific near infrared light absorption properties of blood, the capture procedure for this biometric characteristic is convenient and allows contact-less sensors. However, image skeletons extracted from vein images are often unstable, because the raw vein images suffer from low contrast. We propose a new chain code based feature en- coding method, using spatial and orientation properties of vein patterns, which is capable of dealing with noisy and unstable image skeletons. Chain code comparison and a selection of preprocessing methods have been evaluated in a series of different experiments in single and multi-reference scenarios on two different vein image databases. The experiments showed that chain code comparison outperforms minutiae-based approaches and similarity based mix matching.