James G. Reisman

A hybrid fingerprint matcher

Abstract Most fingerprint matching systems rely on the distribution of minutiae on the fingertip to represent and match fingerprints. While the ridge flow pattern is generally used for classifying fingerprints, it is seldom used for matching. This paper describes a hybrid fingerprint matching scheme that uses both minutiae and ridge flow information to represent and match fingerprints. A set of 8 Gabor filters, whose spatial frequencies correspond to the average inter-ridge spacing in fingerprints, is used to capture the ridge strength at equally spaced orientations. A square tessellation of the filtered images is then used to construct an eight-dimensional feature map, called the ridge feature map. The ridge feature map along with the minutiae set of a fingerprint image is used for matching purposes. The proposed technique has the following features: (i) the entire image is taken into account while constructing the ridge feature map; (ii) minutiae matching is used to determine the translation and rotation parameters relating the query and the template images for ridge feature map extraction; (iii) filtering and ridge feature map extraction are implemented in the frequency domain thereby speeding up the matching process; (iv) filtered query images are catched to greatly increase the one-to-many matching speed. The hybrid matcher performs better than a minutiae-based fingerprint matching system. The genuine accept rate of the hybrid matcher is observed to be ∼10% higher than that of a minutiae-based system at low FAR values. Fingerprint verification (one-to-one matching) using the hybrid matcher on a Pentium III, 800 MHz system takes ∼1.4 s , while fingerprint identification (one-to-many matching) involving 1000 templates takes ∼0.2 s per match.

Fingerprint Matching Using Feature Space Correlation

We present a novel fingerprint alignment and matching scheme that utilizes ridge feature maps to represent, align and match fingerprint images. The technique described here obviates the need for extracting minutiae points or the core point to either align or match fingerprint images. The proposed scheme examines the ridge strength (in local neighborhoods of the fingerprint image) at various orientations, using a set of 8 Gabor filters, whose spatial frequencies correspond to the average inter-ridge spacing in fingerprints. A standard deviation map corresponding to the variation in local pixel intensities in each of the 8 filtered images, is generated. The standard deviation map is sampled at regular intervals in both the horizontal and vertical directions, to construct the ridge feature map. The ridge feature map provides a compact fixed-length representation for a fingerprint image. When a query print is presented to the system, the standard deviation map of the query image and the ridge feature map of the template are correlated, in order to determine the translation offsets necessary to align them. Based on the translation offsets, a matching score is generated by computing the Euclidean distance between the aligned feature maps. Feature extraction and matching takes ~ 1 second in a Pentium III, 800 MHz processor. Combining the matching score generated by the proposed technique with that obtained from a minutiae-based matcher results in an overall improvement in performance of a fingerprint matching system.

Secure fingerprint matching with external registration

Biometrics-based authentication systems offer enhanced security and user convenience compared to traditional token-based (e.g., ID card) and knowledge-based (e.g., password) systems. However, the increased deployment of biometric systems in several commercial and government applications has raised questions about the security of the biometric system itself. Since the biometric traits of a user cannot be replaced if compromised, it is imperative that these systems are suitably secure in order to protect the privacy of the user as well as the integrity of the overall system. In this paper, we first investigate several methods that have been proposed in the literature to increase the security of the templates residing in a biometric system. We next propose a novel fingerprint matching architecture for resource-constrained devices (e.g., smart cards) that ensures the security of the minutiae templates present in the device. Experimental results describing the impact of several system parameters on the matching performance as well as the computational and storage costs are provided. The proposed architecture is shown to enhance the security of the minutiae templates while maintaining the overall matching performance of the system.

Robust local intervertebral disc alignment for spinal MRI

Magnetic resonance (MR) imaging is frequently used to diagnose abnormalities in the spinal intervertebral discs. Owing to the non-isotropic resolution of typical MR spinal scans, physicians prefer to align the scanner plane with the disc in order to maximize the diagnostic value and to facilitate comparison with prior and follow-up studies. Commonly a planning scan is acquired of the whole spine, followed by a diagnostic scan aligned with selected discs of interest. Manual determination of the optimal disc plane is tedious and prone to operator variation. A fast and accurate method to automatically determine the disc alignment can decrease examination time and increase the reliability of diagnosis. We present a validation study of an automatic spine alignment system for determining the orientation of intervertebral discs in MR studies. In order to measure the effectiveness of the automatic alignment system, we compared its performance with human observers. 12 MR spinal scans of adult spines were tested. Two observers independently indicated the intervertebral plane for each disc, and then repeated the procedure on another day, in order to determine the inter- and intra-observer variability associated with manual alignment. Results were also collected for the observers utilizing the automatic spine alignment system, in order to determine the methods consistency and its accuracy with respect to human observers. We found that the results from the automatic alignment system are comparable with the alignment determined by human observers, with the computer showing greater speed and consistency.