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The MBioID initiative has been set up to address the following germane question: What and how biometric technologies could be deployed in identity documents in the foreseeable future? This research effort proposes to look at current and future practices and systems of establishing and using biometric identity documents (IDs) and evaluate their effectiveness in large-scale developments. The first objective of the MBioID project is to present a review document establishing the current state-of-the-art related to the use of multimodal biometrics in an IDs application. This research report gives the main definitions, properties and the framework of use related to biometrics, an overview of the main standards developed in the biometric industry and standardisation organisations to ensure interoperability, as well as some of the legal framework and the issues associated to biometrics such as privacy and personal data protection. The state-of-the-art in terms of technological development is also summarised for a range of single biometric modalities (2D and 3D face, fingerprint, iris, on-line signature and speech), chosen according to ICAO recommendations and availabilities, and for various multimodal approaches. This paper gives a summary of the main elements of that report. The second objective of the MBioID project is to propose relevant acquisition and evaluation protocols for a large-scale deployment of biometric IDs. Combined with the protocols, a multimodal database will be acquired in a realistic way, in order to be as close as possible to a real biometric IDs deployment. In this paper, the issues and solutions related to the acquisition setup are briefly presented.
OBJECTIVE: To design a system of gonioscopy that will allow greater interobserver reliability and more clearly defined screening cutoffs for angle closure than current systems while being simple to teach and technologically appropriate for use in rural Asia, where the prevalence of angle-closure glaucoma is highest. DESIGN: Clinic-based validation and interobserver reliability trial. PARTICIPANTS: Study 1: 21 patients 18 years of age and older recruited from a university-based specialty glaucoma clinic; study 2: 32 patients 18 years of age and older recruited from the same clinic. INTERVENTION: In study 1, all participants underwent conventional gonioscopy by an experienced observer (GLS) using the Spaeth system and in the same eye also underwent Scheimpflug photography, ultrasonographic measurement of anterior chamber depth and axial length, automatic refraction, and biometric gonioscopy with measurement of the distance from iris insertion to Schwalbe's line using a reticule based in the slit-lamp ocular. In study 2, all participants underwent both conventional gonioscopy and biometric gonioscopy by an experienced gonioscopist (NGC) and a medical student with no previous training in gonioscopy (JK). MAIN OUTCOME MEASURES: Study 1: The association between biometric gonioscopy and conventional gonioscopy, Scheimpflug photography, and other factors known to correlate with the configuration of the angle. Study 2: Interobserver agreement using biometric gonioscopy compared to that obtained with conventional gonioscopy. RESULTS: In study 1, there was an independent, monotonic, statistically significant relationship between biometric gonioscopy and both Spaeth angle (P = 0.001, t test) and Spaeth insertion (P = 0.008, t test) grades. Biometric gonioscopy correctly identified six of six patients with occludable angles according to Spaeth criteria. Biometric gonioscopic grade was also significantly associated with the anterior chamber angle as measured by Scheimpflug photography (P = 0.005, t test). In study 2, the intraclass correlation coefficient between graders for biometric gonioscopy (0.97) was higher than for Spaeth angle grade (0.72) or Spaeth insertion grade (0.84). CONCLUSION: Biometric gonioscopy correlates well with other measures of the anterior chamber angle, shows a higher degree of interobserver reliability than conventional gonioscopy, and can readily be learned by an inexperienced observer.
Authentication systems based on biometric features (e.g., fingerprint impressions, iris scans, human face images, etc.) are increasingly gaining widespread use and popularity. Often, vendors and owners of these commercial biometric systems claim impressive performance that is estimated based on some proprietary data. In such situations, there is a need to independently validate the claimed performance levels. System performance is typically evaluated by collecting biometric templates from n different subjects, and for convenience, acquiring multiple instances of the biometric for each of the n subjects. Very little work has been done in 1) constructing confidence regions based on the ROC curve for validating the claimed performance levels and 2) determining the required number of biometric samples needed to establish confidence regions of prespecified width for the ROC curve. To simplify the analysis that address these two problems, several previous studies have assumed that multiple acquisitions of the biometric entity are statistically independent. This assumption is too restrictive and is generally not valid. We have developed a validation technique based on multivariate copula models for correlated biometric acquisitions. Based on the same model, we also determine the minimum number of samples required to achieve confidence bands of desired width for the ROC curve. We illustrate the estimation of the confidence bands as well as the required number of biometric samples using a fingerprint matching system that is applied on samples collected from a small population.
Recent substantive research on biometric analyses of twin and family data has used both a biometric path analysis model (PAM) and a biometric variance components model (VCM). Methodological research on these same topics have suggested benefits of using linear structural equation model algorithms (SEMA) as well as mixed effect multilevel algorithms (MEMA). To better understand the potential similarities and differences among these approaches we first highlight the algebraic equivalence between the standard biometric PAM and the corresponding biometric VCM models for family data. Second, we demonstrate how several SEMA programs based on either the PAM or VCM approach produce equivalent estimates for all phenotypic and biometric parameters. Third, we show how the biometric VCM approach (but not the PAM approach) can be easily programmed using current MEMA programs (e.g., SAS PROC MIXED). We then expand the scope of these different approaches to include measured covariates, observed variable interactions and multiple relatives within each family. MEMA software is compared to SEMA software for programming complex models, including the flexibility of data input, treatment of missing data, inclusion of covariates, and ease of accommodating varying numbers of observations (per family or individual).
Using biometrics for subject verification can significantly improve security over that of approaches based on passwords and personal identification numbers, both of which people tend to lose or forget. In biometric verification the system tries to match an input biometric (such as a fingerprint, face image, or iris image) to a stored biometric template. Thus correlation filter techniques are attractive candidates for the matching precision needed in biometric verification. In particular, advanced correlation filters, such as synthetic discriminant function filters, can offer very good matching performance in the presence of variability in these biometric images (e.g., facial expressions, illumination changes, etc.). We investigate the performance of advanced correlation filters for face, fingerprint, and iris biometric verification.
As biometric recognition techniques are gradually improved, the stability of biometric authentication systems are enhanced. Although bioinformation has properties that make it resistant to fraud, biometric authentication systems are not immune to hacking. We show a secure biometric authentication system (1) to guarantee the integrity of biometric information by mixing data by use of a biometric key and (2) to raise recognition rates by use of bimodal biometrics.
This paper deals with a biometric study of 312 boys and girls, aged 2.5-16 years, living in an area with a long history of pollution by lead. The aim was to search for eventual relationships between ten biometric variables and measures of lead absorption in the bodies, i.e. the amount of lead in the blood (PbB), of these children. Standardized values of the biometric variables were compared in the high-PbB and low-PbB categories, by multivariate analysis of variance. Comparison of the vectors of the ten biometric variables reveals a significant difference between the two categories of PbB levels. We found some evidence that the younger children (below 8 years of age) are more likely to absorb lead in the body and are more vulnerable to the effects of subclinical lead intoxication than their older counterparts. The differences between the averages of biometric variables in the two PbB categories are consistently (although not significantly) greater among younger children. This trend disappeared in the older age group. These results confirm data from the literature that young children are especially at risk. It can be concluded that there is a subtle, but significant, influence of lead absorption on the biometric profiles of children and that this effect is probably more important in children below 8 years of age.
Experiments were undertaken to understand the relationship between dynamic accommodative refractive and biometric (lens thickness (LT), anterior chamber depth (ACD) and anterior segment length (ASL=ACD+LT)) changes during Edinger-Westphal stimulated accommodation in rhesus monkeys. Experiments were conducted on three rhesus monkeys (aged 11.5, 4.75 and 4.75 years) which had undergone prior, bilateral, complete iridectomies and implantation of a stimulating electrode in the Edinger-Westphal (EW) nucleus. Accommodative refractive responses were first measured dynamically with video-based infrared photorefraction and then ocular biometric responses were measured dynamically with continuous ultrasound biometry (CUB) during EW stimulation. The same stimulus amplitudes were used for the refractive and biometric measurements to allow them to be compared. Main sequence relationships (ratio of peak velocity to amplitude) were calculated. Dynamic accommodative refractive changes are linearly correlated with the biometric changes and accommodative biometric changes in ACD, ASL and LT show systematic linear correlations with increasing accommodative amplitudes. The relationships are relatively similar for the eyes of the different monkeys. Dynamic analysis showed that main sequence relationships for both biometry and refraction are linear. Although accommodative refractive changes in the eye occur primarily due to changes in lens surface curvature, the refractive changes are well correlated with A-scan measured accommodative biometric changes. Accommodative changes in ACD, LT and ASL are all well correlated over the full extent of the accommodative response.
Biometric analysis for identity verification is becoming a widespread reality. Such implementations necessitate large-scale capture and storage of biometric data, which raises serious issues in terms of data privacy and (if such data is compromised) identity theft. These problems stem from the essential permanence of biometric data, which (unlike secret passwords or physical tokens) cannot be refreshed or reissued if compromised. Our previously presented biometric-hash framework prescribes the integration of external (password or token-derived) randomness with user-specific biometrics, resulting in bitstring outputs with security characteristics (i.e., noninvertibility) comparable to cryptographic ciphers or hashes. The resultant BioHashes are hence cancellable, i.e., straightforwardly revoked and reissued (via refreshed password or reissued token) if compromised. BioHashing furthermore enhances recognition effectiveness, which is explained in this paper as arising from the Random Multispace Quantization (RMQ) of biometric and external random inputs.
PURPOSE: A classic twin study was undertaken to assess the contribution of genes and environment to the development of refractive errors and ocular biometrics in a twin population. METHODS: A total of 1224 twins (345 monozygotic [MZ] and 267 dizygotic [DZ] twin pairs) aged between 18 and 88 years were examined. All twins completed a questionnaire consisting of a medical history, education, and zygosity. Objective refraction was measured in all twins, and biometric measurements were obtained using partial coherence interferometry. RESULTS: Intrapair correlations for spherical equivalent and ocular biometrics were significantly higher in the MZ than in the DZ twin pairs (P < 0.05), when refraction was considered as a continuous variable. A significant gender difference in the variation of spherical equivalent and ocular biometrics was found (P < 0.05). A genetic model specifying an additive, dominant, and unique environmental factor that was sex limited was the best fit for all measured variables. Heritability of spherical equivalents of 88% and 75% were found in the men and women, respectively, whereas, that of axial length was 94% and 92%, respectively. Additive genetic effects accounted for a greater proportion of the variance in spherical equivalent, whereas the variance in ocular biometrics, particularly axial length was explained mostly by dominant genetic effects. CONCLUSIONS: Genetic factors, both additive and dominant, play a significant role in refractive error (myopia and hypermetropia) as well as in ocular biometrics, particularly axial length. The sex limitation ADE model (additive genetic, nonadditive genetic, and environmental components) provided the best-fit genetic model for all parameters.
OBJECTIVE: To study the effects of maternal and pregnancy characteristics on fetal biometric size using longitudinal ultrasound measurements and to construct customized models for fetal biometric size charts. METHODS: A cohort of 533 healthy pregnant women with normal singleton pregnancies were recruited for regular ultrasound examination for fetal biometry between 24 and 40 weeks' gestation. Multilevel modeling was used to construct models of fetal head size, femur length and abdominal circumference. Variables of maternal and pregnancy characteristics including booking weight and height, age, parity and fetal sex were included in the construction of the customized fetal biometric size charts. RESULTS: Increased fetal head size and abdominal circumference were significantly associated with extremes of maternal age. Maternal height had a statistically significant influence on biparietal diameter. Maternal booking weight had an influence on fetal abdominal circumference and femur length. Fetal sex was found to have a statistically significant influence on the final regression models of biparietal diameter, head circumference and femur length. Parity had an influence on fetal head circumference and abdominal circumference. CONCLUSIONS: Maternal and pregnancy characteristics have a significant influence on in-utero fetal biometry. We produced models to construct customized fetal biometric size charts. Further validation studies are necessary to evaluate the clinical usefulness of such customized fetal biometric size charts.
In prior research we have shown how linear structural equation models and computer programs (e.g., LISREL) may be simply and directly used to provide alternatives for the traditional biometric twin design. We use structural equations and path models to define biometric group differences, we write traditional common-factor models in the same way, and then we take a detailed look at some alternative multivariate and biometric models. We contrast the biometric-factors covariance structure approach used by Loehlin and Vandenberg (1968), Martin and Eaves (1977), and others with the psychometric-factors approach used by McArdle et al. (1980) and others. We use the multivariate primary mental abilities data on monozygotic (MZ) and dizygotic (DZ) twins from Loehlin and Vandenberg (1968) to detail fundamental differences in model specification and results. We extend both multivariate biometric approaches using exploratory and confirmatory multiple-factor models. These comparisons show that each alternative multivariate methodology has useful features for empirical applications.
The acute toxic class (ATC) methods were developed for determining LD(50)/LC(50) estimates of chemical substances with significantly fewer animals than needed when applying conventional LD(50)/LC(50) tests. The ATC methods are sequential stepwise procedures with fixed starting doses/concentrations and a maximum of six animals used per dose/concentration. The numbers of dead/moribund animals determine whether further testing is necessary or whether the test is terminated. In recent years we have developed classification procedures for the oral, dermal and inhalation routes of administration by using biometric methods. The biometric approach assumes a probit model for the mortality probability of a single animal and assigns the chemical to that toxicity class for which the best concordance is achieved between the statistically expected and the observed numbers of dead/moribund animals at the various steps of the test procedure. In previous publications we have demonstrated the validity of the biometric ATC methods on the basis of data obtained for the oral ATC method in two-animal ring studies with 15 participants from six countries. Although the test procedures and biometric evaluations for the dermal and inhalation ATC methods have already been published, there was a need for an adaptation of the classification schemes to the starting doses/concentrations of the Globally Harmonized Classification System (GHS) recently adopted by the Organization for Economic Co-operation and Development (OECD). Here we present the biometric evaluation of the dermal and inhalation ATC methods for the starting doses/concentrations of the GHS and of some other international classification systems still in use. We have developed new test procedures and decision rules for the dermal and inhalation ATC methods, which require significantly fewer animals to provide predictions of toxicity classes, that are equally good or even better than those achieved by using the conventional LD(50)/LC(50) methods. In order to cope with rather narrow dose/concentration classes of the GHS we have, as in our previous publications, combined the outcome of all results that can be obtained during testing for the allocation to one of the defined toxicity classes of the GHS. Our results strongly recommend the deletion of the dermal LD(50) and the inhalation LC(50) test as regulatory tests and the adoption of the dermal and inhalation ATC methods as internationally accepted alternatives.
We examine the performance of multimodal biometric authentication systems using state-of-the-art Commercial Off-the-Shelf (COTS) fingerprint and face biometric systems on a population approaching 1,000 individuals. The majority of prior studies of multimodal biometrics have been limited to relatively low accuracy non-COTS systems and populations of a few hundred users. Our work is the first to demonstrate that multimodal fingerprint and face biometric systems can achieve significant accuracy gains over either biometric alone, even when using highly accurate COTS systems on a relatively large-scale population. In addition to examining well-known multimodal methods, we introduce new methods of normalization and fusion that further improve the accuracy.
At the core of contemporary morphometrics--the quantitative study of biological shape variation--is a synthesis of two originally divergent methodological styles. One contributory tradition is the multivariate analysis of covariance matrices originally developed as biometrics and now dominant across a broad expanse of applied statistics. This approach, couched solely in the linear geometry of covariance structures, ignores biomathematical aspects of the original measurements. The other tributary emphasizes the direct visualization of changes in biological form. However, making objective the biological meaning of the features seen in those diagrams was always problematical; also, the representation of variation, as distinct from pairwise difference, proved infeasible. To combine these two variants of biomathematical modeling into a valid praxis for quantitative studies of biological shape was a goal earnestly sought though most of this century. That goal was finally achieved in the 1980s when techniques from mathematical statistics, multivariate biometrics, non-Euclidean geometry and computer graphics were combined in a coherent new system of tools for the complete regionalized quantitative analysis of landmark points together with the biomedical images in which they are seen. In this morphometric synthesis, correspondence of landmarks (biologically labeled geometric points, like "bridge of the nose") across specimens is taken as a biomathematical primitive. The shapes of configurations of landmarks are defined as equivalence classes with respect to the Euclidean similarity group and then represented as single points in David Kendall's shape space, a Riemannian manifold with Procrustes distance as metric. All conventional multivariate strategies carry over to the study of shape variation and covariation when shapes are interpreted in the tangent space to the shape manifold at an average shape. For biomathematical interpretation of such analyses, one needs a basis for the tangent space compatible with the reality of local biotheoretical processes and explanations at many different geometric scales, and one needs graphics for visualizing average shape differences and other statistical contrasts there. Both of these needs are managed by the thin-plate spline, a deformation function that has an unusually helpful linear algebra. The spline also links the biometrics of landmarks to deformation analysis of the images from which the landmarks originally arose. This article reviews the history and principal tools of this synthesis in their biomathematical and biometrical context and demonstrates their usefulness in a study of focal neuroanatomical anomalies in schizophrenia.