Law enforcement agencies around the world use ridge-based biometrics, especially fingerprints, to fight crime. Fingermarks that are left at a crime scene and identified as potentially having evidential value (EV) in a court of law are recorded for further forensic analysis. Here, we test our evidential value algorithm (EVA) which uses image features trained on forensic expert decisions for 1428 fingermarks to produce an EV score for an image. First, we study the relationship between whether a fingermark is assessed as having EV, either by a human expert or by EVA, and its correct and confident identification by an automatic identification system. In particular, how often does an automatic system achieve identification when the mark is assessed as not having evidential value? We show that when the marks are captured by a mobile phone, correct and confident automatic matching occurs for 257 of the 1428. Of these, 236 were marked as having sufficient EV by experts and 242 by EVA thresholded on equal error rate. Second, we test four relatively challenging ridge-based biometric databases and show that EVA can be successfully applied to give an EV score to all images. Using EV score as an image quality value, we show that in all databases, thresholding on EV improves performance in closed set identification. Our results suggest an EVA application that filters fingermarks meeting a minimum EV score could aid forensic experts at the point of collection, or by flagging difficult latents objectively, or by pre-filtering specimens before submission to an AFIS.

We present a graphical representation for palm vein patterns for use as biometric identifiers. The palm vein image captured from an infra red camera is converted into a spatial graph. After image enhancement and binarisation, the palm vein features are extracted from the skeleton using a novel two stage spur removal technique. The location of the features and the connections between them are used to define a Palm Vein Graph. Palm vein graphs are compared using the Biometric Graph Matching (BGM) Algorithm. We propose a graph registration algorithm that improves over existing state of the art algorithms for graph registration. We introduce 10 graph topology-based measures for comparing palm vein graphs. Experiments are conducted on a public palm vein database. One of the introduced measures, an edge-based similarity, gave a definite improvement in matching accuracies over other published results on the same database, especially for samples with only a small common overlap area due to displacement. In addition, when the edge-based measure was combined with one of three other topological features, we demonstrate a further improvement in matching accuracy.

In this paper we investigate two real crime-related networks, which are both bipartite. The bipartite networks are: a spatial network where crimes of various types are committed in different local government areas; and a dark terrorist network where individuals attend events or have common affiliations. In each case we analyse the communities found by a random-walk based algorithm in the primary weighted projection network. We demonstrate that the identified communities represent meaningful information, and in particular, that the small communities found in the terrorist network represent meaningful cliques.

Medical staff around the world must take reasonable steps to identify newborns and infants clearly, so as to prevent mix-ups, and to ensure the correct medication reaches the correct child. Footprints are frequently taken despite verification with footprints being challenging due to strong noise. The noise is introduced by the tininess of the structures, movement during capture, and the infant's rapid growth. In this article we address the image processing part of the problem and introduce a novel algorithm for the extraction of creases from infant footprints. The algorithm uses directional filtering on different resolution levels, morphological processing, and block-wise crease line reconstruction. We successfully test our method on noise-affected infant footprints taken from the same infants at different ages.

This paper presents an automatic retina verification framework based on the biometric graph matching (BGM) algorithm. The retinal vasculature is extracted using a family of matched filters in the frequency domain and morphological operators. Then, retinal templates are defined as formal spatial graphs derived from the retinal vasculature. The BGM algorithm, a noisy graph matching algorithm, robust to translation, non-linear distortion, and small rotations, is used to compare retinal templates. The BGM algorithm uses graph topology to define three distance measures between a pair of graphs, two of which are new. A support vector machine (SVM) classifier is used to distinguish between genuine and imposter comparisons. Using single as well as multiple graph measures, the classifier achieves complete separation on a training set of images from the VARIA database (60% of the data), equaling the state-of-the-art for retina verification. Because the available data set is small, kernel density estimation (KDE) of the genuine and imposter score distributions of the training set are used to measure performance of the BGM algorithm. In the one dimensional case, the KDE model is validated with the testing set. A 0 EER on testing shows that the KDE model is a good fit for the empirical distribution. For the multiple graph measures, a novel combination of the SVM boundary and the KDE model is used to obtain a fair comparison with the KDE model for the single measure. A clear benefit in using multiple graph measures over a single measure to distinguish genuine and imposter comparisons is demonstrated by a drop in theoretical error of between 60% and more than two orders of magnitude.

We represent the retina vessel pattern as a spatial relational graph, and match features using error-correcting graph matching. We study the distinctiveness of the nodes (branching and crossing points) compared with that of the edges and other substructures (nodes of degree k, paths of length k). On a training set from the VARIA database, we show that as well as nodes, three other types of graph sub structure completely or almost completely separate genuine from imposter comparisons. We show that combining nodes and edges can improve the separation distance. We identify two retina graph statistics, the edge-to-node ratio and the variance of the degree distribution, that have low correlation with node match score.

Abstract Fingerprint biometric authentication has particular advantages in a highly mobile environment. We investigate design issues involved in building authentication systems using minutia‐based fingerprint templates, where the template is protected during comparison as well as storage. Two popular bio‐cryptographic schemes based on the set difference metric, the Fuzzy Vault and PinSketch, are analysed with regard to theoretical bounds on the template sizes and decision thresholds. We define six different minutiae‐based templates and for each, quantisation parameters are determined that yield the best matching performance at a threshold where the probability of false match is zero. We then determine which, if any, of the representations satisfy the theoretical bounds proposed for each bio‐cryptographic construct. We implement a PinSketch‐based authentication system that uses a combination of a commonality and a set difference measure to securely compare two fingerprint templates, with negligible deterioration in accuracy. Our results indicate that to securely correct the degree of intra‐sample error observed in minutiae‐based templates, efficient commonality‐based error tolerant cryptographic constructs will be more suited than set difference based constructs. Copyright © 2010 John Wiley & Sons, Ltd.

This paper studies the amount of distinctive information contained in a privacy protecting and compact template of a retinal image created from the locations of crossings and bifurcations in the choroidal vasculature, otherwise called feature points. Using a training set of 20 different retina, we build a template generator that simulates one million imposter comparisons and computes the number of imposter retina comparisons that successfully matched at various thresholds. The template entropy thus computed was used to validate a theoretical model of imposter comparisons. The simulator and the model both estimate that 20 bits of entropy can be achieved by the feature point-based template. Our results reveal the distinctiveness of feature point-based retinal templates, hence establishing their potential as a biometric identifier for high security and memory intensive applications.

We analyse the numbers and representatives of all bundles of presemifields in the isotopism class of GF(p3), for application to the search for Hadamard codes and differentially uniform functions.

The class of generalised Hadamard transforms includes the Fourier, generalised, discrete Fourier, Walsh-Hadamard, complex Hadamard and reverse jacket transforms. The generalised Hadamard transforms may by partly classified by signal length, by group of entries in the transform matrix and by a recently introduced third parameter, the jacket width of the transform matrix. Here we introduce a weighted trace map, which realises the Fourier transform as an exponential weighted sum of Galois ring traces. We give examples of Fourier transforms with jacket width 0, jacket width 1 and maximum jacket width (half the signal length). We show the Fourier transforms of length 4kwith entries in {plusmn1, plusmni} obtained using the weighted trace map from the Galois ring GR(4,k) have jacket width 2k-1

A generalised Hadamard transform for multiphase or multilevel signals is introduced, which includes the Fourier, generalised, discrete Fourier, Walsh-Hadamard and reverse jacket transforms. The jacket construction is formalised and shown to admit a tensor product decomposition. Primary matrices under this decomposition are identified. New examples of primary jacket matrices of orders 8 and 12 are presented

We demonstrate that many well-known binary, quaternary, and q-ary codes are cocyclic Hadamard codes; that is, derived from a cocyclic generalized Hadamard matrix or its equivalents. Nonlinear cocyclic Hadamard codes meet the generalized Plotkin bound. Using presemifield multiplication cocycles, we construct new equivalence classes of cocyclic Hadamard codes which meet the Plotkin bound.