Descriptors for image-based fingerprint matchers

• Authors: Loris Nanni;Alessandra Lumini
• Venue: Expert Systems with Applications: An International Journal
• Year: 2009

This paper focuses on the use of image-based techniques in fingerprint verification. A detailed review of the existing literature is provided by classifying existing methods on the basis of their alignment procedure and discussing the most salient approaches and their pros and cons. Even if, at present, the image-based techniques do not gain performance comparable with that obtained by the best minutiae-based approaches, several good reasons can be listed to support the research on image-based approaches: the possibility of using additional features in combination with minutiae to improve verification performance, the availability of a fixed length feature vector which makes these approaches suitable to be indexed, to be coupled with a learning system or to be combined with tokenised random number in a two factor authentication system (Biohashing). In this work we compare several texture-based descriptors for fingerprints and propose a novel image-based fingerprint matcher based on the minutiae alignment. In this approach, the feature extraction is performed locally on a decomposition of the fingerprint in several overlapping sub-windows considering the following measures: Gabor filters descriptors, invariant local binary patterns and histogram of gradients. Moreover, we propose to perform a supervised selection of a small subset of descriptors, in order to reduce the dimensionality of the feature set and discarding the less discriminative features. Extensive experiments conducted over the four FVC2002 fingerprint databases using a blind testing protocol show that the proposed system dramatically outperforms the other image-based fingerprint matchers proposed in the literature. Moreover, a further experiment conducted on a set of images reconstructed from ISO templates show that, differently to the minutiae-based approaches, our image-based matcher cannot be faked with the sole knowledge of the minutiae position and orientation, at least the original orientation image is required in order have a chance of performing a successful attack.