IMPROVING THE RIGOR OF THE LATENT PRINT EXAMINATION PROCESS

This PhD thesis is a synthesis of a portfolio of interrelated previously published work that was conducted to improve the rigor, standardization, transparency, and quantifiability of the latent print examination process. The core of the work relates to the development, adoption, and implications of the Extended Feature Set (EFS). EFS is a formal international standard (incorporated in ANSI/NIST-ITL) that defines a method of characterizing the information content of friction ridge impressions — allowing latent print examiners to unambiguously document the bases of their determinations during examination. EFS is the enabling technology that has made all of the other elements of this portfolio of work possible: evaluations of the accuracy and reliability of latent print examiners’ determinations, evaluations of the reliability of examiners’ feature markup, evaluations of examiners’ assessments of sufficiency, evaluations of latent print quality, development of quality and distortion metrics, evaluations of AFIS accuracy, and the development of training materials to assist in improving the uniformity of examiners’ annotations of the features and attributes of friction ridge impressions. The thesis summarizes these previous publications, as well as discussing their implications and possible future research and tools that could leverage this body of work. -- Cette recherche doctorale présente la synthèse d’un portfolio de travaux et de publications ayant pour objectif d’améliorer la rigueur, la standardisation, la transparence et la quantification dans le cadre du processus d’identification des traces papillaires. L’élément fondateur de cette recherche est le développement, l’adoption et les implications du Extended Feature Set (EFS). EFS est un standard formel international (incorporé dans ANSI/NIST-ITL) qui définit la méthode de description des caractéristiques présentes sur les impressions papillaires. Il permet aux experts en lophoscopie de documenter de manière non-ambiguë les observations qui sont à la base des conclusions formulées à la suite des examens. EFS a été le facilitateur qui a rendu possible tous les autres éléments de ce portfolio de recherches, à savoir : l’évaluation de la fiabilité et l’exactitude des conclusions des experts en matière de traces papillaires, l’évaluation de la fidélité des annotations des experts, le développement de mesures de qualité et de la distorsion des traces, l’évaluation de l’exactitude des systèmes AFIS et finalement le développement d’une formation visant à améliorer la reproductibilité, entre experts, des annotations des caractéristiques papillaires et de leurs attributs. Cette recherche doctorale présente une synthèse de l’ensemble de ces travaux publiés et discute des implications de ceux-ci, des voies de recherche future ainsi que les outils qui pourraient y être associés

Reconocimiento de huellas dactilares para aplicaciones forenses

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Tecnología Electrónica y de las Comunicaciones. Fecha de lectura: mayo de 2015The author was awarded with a European Commission Marie Curie Fellowship under the Innovative Training Networks (ITN) in the project Bayesian Biometrics for Forensics (BBfor2, FP7-PEOPLE-ITN-2008) under Grant Agreement number 238803 between 2011 and 2013. The author was also funded through the European Union Project - Biometrics Evaluation and Testing (BEAT) for 2014 and 2015 which supported the research summarized in this Dissertatio

Facilitating sensor interoperability and incorporating quality in fingerprint matching systems

This thesis addresses the issues of sensor interoperability and quality in the context of fingerprints and makes a three-fold contribution. The first contribution is a method to facilitate fingerprint sensor interoperability that involves the comparison of fingerprint images originating from multiple sensors. The proposed technique models the relationship between images acquired by two different sensors using a Thin Plate Spline (TPS) function. Such a calibration model is observed to enhance the inter-sensor matching performance on the MSU dataset containing images from optical and capacitive sensors. Experiments indicate that the proposed calibration scheme improves the inter-sensor Genuine Accept Rate (GAR) by 35% to 40% at a False Accept Rate (FAR) of 0.01%. The second contribution is a technique to incorporate the local image quality information in the fingerprint matching process. Experiments on the FVC 2002 and 2004 databases suggest the potential of this scheme to improve the matching performance of a generic fingerprint recognition system. The final contribution of this thesis is a method for classifying fingerprint images into 3 categories: good, dry and smudged. Such a categorization would assist in invoking different image processing or matching schemes based on the nature of the input fingerprint image. A classification rate of 97.45% is obtained on a subset of the FVC 2004 DB1 database

Fingerabdruckswachstumvorhersage, Bildvorverarbeitung und Multi-level Judgment Aggregation

Im ersten Teil dieser Arbeit wird Fingerwachstum untersucht und eine Methode zur Vorhersage von Wachstum wird vorgestellt. Die Effektivität dieser Methode wird mittels mehrerer Tests validiert. Vorverarbeitung von Fingerabdrucksbildern wird im zweiten Teil behandelt und neue Methoden zur Schätzung des Orientierungsfelds und der Ridge-Frequenz sowie zur Bildverbesserung werden vorgestellt: Die Line Sensor Methode zur Orientierungsfeldschätzung, gebogene Regionen zur Ridge-Frequenz-Schätzung und gebogene Gabor Filter zur Bildverbesserung. Multi-level Jugdment Aggregation wird eingeführt als Design Prinzip zur Kombination mehrerer Methoden auf mehreren Verarbeitungsstufen. Schließlich wird Score Neubewertung vorgestellt, um Informationen aus der Vorverarbeitung mit in die Score Bildung einzubeziehen. Anhand eines Anwendungsbeispiels wird die Wirksamkeit dieses Ansatzes auf den verfügbaren FVC-Datenbanken gezeigt.Finger growth is studied in the first part of the thesis and a method for growth prediction is presented. The effectiveness of the method is validated in several tests. Fingerprint image preprocessing is discussed in the second part and novel methods for orientation field estimation, ridge frequency estimation and image enhancement are proposed: the line sensor method for orientation estimation provides more robustness to noise than state of the art methods. Curved regions are proposed for improving the ridge frequency estimation and curved Gabor filters for image enhancement. The notion of multi-level judgment aggregation is introduced as a design principle for combining different methods at all levels of fingerprint image processing. Lastly, score revaluation is proposed for incorporating information obtained during preprocessing into the score, and thus amending the quality of the similarity measure at the final stage. A sample application combines all proposed methods of the second part and demonstrates the validity of the approach by achieving massive verification performance improvements in comparison to state of the art software on all available databases of the fingerprint verification competitions (FVC)

Interpol review of fingermarks and other body impressions 2016–2019

This review paper covers the forensic-relevant literature in fingerprint and bodily impression sciences from 2016 to 2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/ 14458/file/Interpol%20 Review%20 Papers%202019. pdf

Analysis Of Data Stratification In A Multi-Sensor Fingerprint Dataset Using Match Score Statistics

Biometric data is an essential feature employed in testing the performance of any real time biometric recognition system prior to its usage. The variations introduced in the match performance critically determine the authenticity of the biometric data to be able to be used in an everyday scenario for the testing of biometric verification systems. This study in totality aims at understanding the impact of data stratification of a such a biometric test dataset on the match performance of each of its stratum. In order to achieve this goal, the fingerprint dataset of the West Virginia University\u27s 2012 BioCOP has been employed which is a part of the many multimodal biometric data collection projects that the University has accomplished. This test dataset has been initially segmented based on the scanners employed in the process of data acquisition to check for the variations in match performance with reference to the acquisition device. The secondary stage of data stratification included the creation of stratum based on the demographic features of the subjects in the dataset.;The main objectives this study aims to achieve are:;• Developing a framework to assess the match score distributions of each stratum..;• Assessing the match performance of demographic strata in comparison to the total dataset..;• Statistical match performance evaluation using match score statistics..;Following the generation of genuine and imposter match score distributions , Receiver Operating Characteristic Curves (ROC) were plotted to compare the match performance of each demographic stratum with respect to the total dataset. The divergence measures KLD and JSD have been calculated which signify the amount of variation between the match score distributions of each stratum. With the help of these procedures, the task of estimating the effect of data stratification on the match performance has been accomplished which serves as a measure of understanding the impact of this fingerprint dataset when used for biometric testing purposes