Download or read book Machine Learning in Fingerprint Probability Evaluation written by Chang Su and published by . This book was released on 2011 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although fingerprints have been used in forensic identification for over a century, establishing the degree of uniqueness a given fingerprint has remained elusive since it involves relationships and correlations hidden in a large amount of fingerprint data. We develop machine learning approaches to this problem focusing on two aspects: better generative models for fingerprints, and estimating probabilistic metrics for individuality and rarity. Generative approaches are used to evaluate fingerprint Individuality, defined as the probability of random correspondence (PRC) within a tolerance. The evaluation uses Bayesian networks and three fingerprint representations: ridge flow, minutiae, and ridge points. Mixture models of features are used, with parameters estimated using the EM algorithm. Fingerprint PRCs are determined for given numbers of available and matching minutiae. A Bayesian method based on graphical models is introduced to compute fingerprint rarity. The model is able to handle the large number of variables and the complexity of the distributions. Since latent prints are often incomplete and the core point may be missing in the field of view, a machine learning approach based on Gaussian process regression is proposed to predicate the core point. The coordinate system is transformed into standard position based on finding the core point. A graphical model, which takes into account inter-minutia dependencies and minutia confidences, is used to determine evidence probability from which the specific probability of match among n is evaluated. To improve the accuracy of rarity estimation for low quality latent prints, a fully Bayesian treatment allows considering core point uncertainty. The generative model is validated using a goodness-of-fit test. Rarity evaluation is illustrated using several examples, including simple configurations of minutiae, randomly selected latent fingerprints in a database, and a well-known case of erroneous identification.

Download or read book Handbook of Fingerprint Recognition written by Davide Maltoni and published by Springer Nature. This book was released on 2022-07-04 with total page 541 pages. Available in PDF, EPUB and Kindle. Book excerpt: A major new professional reference work on fingerprint security systems and technology from leading international researchers in the field. Handbook provides authoritative and comprehensive coverage of all major topics, concepts, and methods for fingerprint security systems. This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators.

Download or read book Biometric System and Data Analysis written by Ted Dunstone and published by Springer Science & Business Media. This book was released on 2008-10-31 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluating, interpreting and understanding biometric data. It naturally leads to topics including data mining and prediction to be examined in detail. The book places an emphasis on the various performance measures available for biometric systems, what they mean, and when they should and should not be applied. The evaluation techniques are presented rigorously, however they are always accompanied by intuitive explanations. This is important for the increased acceptance of biometrics among non-technical decision makers, and ultimately the general public.

Download or read book Pattern Recognition Machine Intelligence and Biometrics written by Patrick S. P. Wang and published by Springer Science & Business Media. This book was released on 2012-02-13 with total page 883 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Pattern Recognition, Machine Intelligence and Biometrics" covers the most recent developments in Pattern Recognition and its applications, using artificial intelligence technologies within an increasingly critical field. It covers topics such as: image analysis and fingerprint recognition; facial expressions and emotions; handwriting and signatures; iris recognition; hand-palm gestures; and multimodal based research. The applications span many fields, from engineering, scientific studies and experiments, to biomedical and diagnostic applications, to personal identification and homeland security. In addition, computer modeling and simulations of human behaviors are addressed in this collection of 31 chapters by top-ranked professionals from all over the world in the field of PR/AI/Biometrics. The book is intended for researchers and graduate students in Computer and Information Science, and in Communication and Control Engineering. Dr. Patrick S. P. Wang is a Professor Emeritus at the College of Computer and Information Science, Northeastern University, USA, Zijiang Chair of ECNU, Shanghai, and NSC Visiting Chair Professor of NTUST, Taipei.

Download or read book Deep Learning for the Analysis of Latent Fingerprint Images written by Jude C. Ezeobiejesi and published by . This book was released on 2019 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation proposes deep learning models and algorithms developed in the context of machine learning for automatic latent fingerprint image quality assessment, quality improvement, segmentation and matching. We also propose techniques that help speed-up convergence of a deep neural network and achieve a better estimation of the relation between a latent fingerprint image patch and its target class. A unified frequency domain based framework for latent fingerprint matching using image patches, as well as a novel latent fingerprint super-resolution model that uses a graph-total variation energy of latent fingerprints as a non-local regularizer for learning optimal weights for high quality image reconstruction, are also proposed. Using the deep learning models, we aim at providing an end-to-end automatic system that solves the problems inherent in latent fingerprint quality assessment, quality improvement, segmentation and matching.

Download or read book Machine Learning and Knowledge Extraction written by Andreas Holzinger and published by Springer Nature. This book was released on 2019-08-22 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the IFIP TC 5, TC 12, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2019, held in Canterbury, UK, in August 2019. The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.

Download or read book Computational Algorithms for Fingerprint Recognition written by Bir Bhanu and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biometrics such as fingerprint, face, gait, iris, voice and signature, recognizes one's identity using his/her physiological or behavioral characteristics. Among these biometric signs, fingerprint has been researched the longest period of time, and shows the most promising future in real-world applications. However, because of the complex distortions among the different impressions of the same finger, fingerprint recognition is still a challenging problem. Computational Algorithms for Fingerprint Recognition presents an entire range of novel computational algorithms for fingerprint recognition. These include feature extraction, indexing, matching, classification, and performance prediction/validation methods, which have been compared with state-of-art algorithms and found to be effective and efficient on real-world data. All the algorithms have been evaluated on NIST-4 database from National Institute of Standards and Technology (NIST). Specific algorithms addressed include: -Learned template based minutiae extraction algorithm, -Triplets of minutiae based fingerprint indexing algorithm, -Genetic algorithm based fingerprint matching algorithm, -Genetic programming based feature learning algorithm for fingerprint classification, -Comparison of classification and indexing based approaches for identification, -Fundamental fingerprint matching performance prediction analysis and its validation. Computational Algorithms for Fingerprint Recognition is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a secondary text for graduate-level students in computer science and engineering.

Download or read book Statistical Machine Learning for Human Behaviour Analysis written by Thomas Moeslund and published by MDPI. This book was released on 2020-06-17 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Special Issue focused on novel vision-based approaches, mainly related to computer vision and machine learning, for the automatic analysis of human behaviour. We solicited submissions on the following topics: information theory-based pattern classification, biometric recognition, multimodal human analysis, low resolution human activity analysis, face analysis, abnormal behaviour analysis, unsupervised human analysis scenarios, 3D/4D human pose and shape estimation, human analysis in virtual/augmented reality, affective computing, social signal processing, personality computing, activity recognition, human tracking in the wild, and application of information-theoretic concepts for human behaviour analysis. In the end, 15 papers were accepted for this special issue. These papers, that are reviewed in this editorial, analyse human behaviour from the aforementioned perspectives, defining in most of the cases the state of the art in their corresponding field.

Download or read book New Solutions for an Old Challenge written by Ronny Merkel and published by Logos Verlag Berlin GmbH. This book was released on 2014 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: In criminal investigations, latent fingerprints are often considered as reliable means of identifying suspects. However, the evidential value of a print is strongly dependent on the knowledge of its age (the time which has passed since deposition). Suspects might admit their previous presence at a crime scene, but often claim to have been there prior to or after the crime. Especially in regard to public or highly-frequented crime scenes, prints might lose their evidential value in this case, potentially leading to dropped charges. Despite its high relevance, the challenge of estimating a latent print's age could not be adequately addressed for 80 years. In this thesis, non-invasive high-resolution capturing devices are for the first time applied to the age estimation challenge, replacing classical physical or chemical print development techniques. They allow to capture a single print in regular time intervals and to systematically study its degradation behavior. Introducing automated processing methods in the form of a digital pipeline including preprocessing, feature extraction and age estimation techniques, objective age estimates are presented for the first time in this field. Maximum classification performances of different capturing devices between 76% and 86% are achieved for two-class problems. Furthermore, a qualitative influence model on the aging speed of latent prints is designed, forming a prerequisite for future studies.

Download or read book Computational Methods in Biometric Authentication written by Michael E. Schuckers and published by Springer Science & Business Media. This book was released on 2010-06-03 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biometrics, the science of using physical traits to identify individuals, is playing an increasing role in our security-conscious society and across the globe. Biometric authentication, or bioauthentication, systems are being used to secure everything from amusement parks to bank accounts to military installations. Yet developments in this field have not been matched by an equivalent improvement in the statistical methods for evaluating these systems. Compensating for this need, this unique text/reference provides a basic statistical methodology for practitioners and testers of bioauthentication devices, supplying a set of rigorous statistical methods for evaluating biometric authentication systems. This framework of methods can be extended and generalized for a wide range of applications and tests. This is the first single resource on statistical methods for estimation and comparison of the performance of biometric authentication systems. The book focuses on six common performance metrics: for each metric, statistical methods are derived for a single system that incorporates confidence intervals, hypothesis tests, sample size calculations, power calculations and prediction intervals. These methods are also extended to allow for the statistical comparison and evaluation of multiple systems for both independent and paired data. Topics and features: * Provides a statistical methodology for the most common biometric performance metrics: failure to enroll (FTE), failure to acquire (FTA), false non-match rate (FNMR), false match rate (FMR), and receiver operating characteristic (ROC) curves * Presents methods for the comparison of two or more biometric performance metrics * Introduces a new bootstrap methodology for FMR and ROC curve estimation * Supplies more than 120 examples, using publicly available biometric data where possible * Discusses the addition of prediction intervals to the bioauthentication statistical toolset * Describes sample-size and power calculations for FTE, FTA, FNMR and FMR Researchers, managers and decisions makers needing to compare biometric systems across a variety of metrics will find within this reference an invaluable set of statistical tools. Written for an upper-level undergraduate or master’s level audience with a quantitative background, readers are also expected to have an understanding of the topics in a typical undergraduate statistics course. Dr. Michael E. Schuckers is Associate Professor of Statistics at St. Lawrence University, Canton, NY, and a member of the Center for Identification Technology Research.

Download or read book Segmentation and Separation of Overlapped Latent Fingerprints written by Branka Stojanović and published by Springer Nature. This book was released on 2019-10-22 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Springerbrief presents an overview of problems and technologies behind segmentation and separation of overlapped latent fingerprints, which are two fundamental steps in the context of fingerprint matching systems. It addresses five main aspects: (1) the need for overlapped latent fingerprint segmentation and separation in the context of fingerprint verification systems; (2) the different datasets available for research on overlapped latent fingerprints; (3) selected algorithms and techniques for segmentation of overlapped latent fingerprints; (4) selected algorithms and techniques for separation of overlapped latent fingerprints; and (5) the use of deep learning techniques for segmentation and separation of overlapped latent fingerprints. By offering a structured overview of the most important approaches currently available, putting them in perspective, and suggesting numerous resources for further exploration, this book gives its readers a clear path for learning new topics and engaging in related research. Written from a technical perspective, and yet using language and terminology accessible to non-experts, it describes the technologies, introduces relevant datasets, highlights the most important research results in each area, and outlines the most challenging open research questions. This Springerbrief targets researchers, professionals and advanced-level students studying and working in computer science, who are interested in the field of fingerprint matching and biometrics. Readers who want to deepen their understanding of specific topics will find more than one hundred references to additional sources of related information.

Download or read book Fundamentals of Fingerprint Analysis written by Hillary Moses Daluz and published by CRC Press. This book was released on 2014-12-01 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: The "CSI effect" has brought an explosion of interest in the forensic sciences, leading to the development of new programs in universities across the world. While dozens of professional texts on the science of fingerprint analysis are available, few are designed specifically for students. An essential learning tool for classes in fingerprinting and impression evidence, Fundamentals of Fingerprint Analysis takes students from an understanding of the historical background of fingerprint evidence to seeing how it plays out in a present-day courtroom. Using a pedagogical format, with each chapter building on the previous one, the book is divided into three sections. The first explains the history and theory of fingerprint analysis, fingerprint patterns and classification, and the concept of biometrics—the practice of using unique biological measurements or features to identify individuals. The second section discusses forensic light sources and physical and chemical processing methods. Section Three covers fingerprint analysis with chapters on documentation, crime scene processing, fingerprint and palm print comparisons, and courtroom testimony. Designed for classroom use, each chapter contains key terms, learning objectives, a chapter summary, and review questions to test students’ assimilation of the material. Ample diagrams, case studies, and photos demonstrate concepts in a way that prepares students for working actual cases.

Download or read book Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint written by Mark K. Hinders and published by Springer Nature. This book was released on 2020-07-01 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify features for machine learning and pattern classification in time-domain signals. Whether for medical imaging or structural health monitoring, it develops analysis techniques and measurement technologies for the quantitative characterization of materials, tissues and structures by non-invasive means. Intelligent Feature Selection for Machine Learning using the Dynamic Wavelet Fingerprint begins by providing background information on machine learning and the wavelet fingerprint technique. It then progresses through six technical chapters, applying the methods discussed to particular real-world problems. Theses chapters are presented in such a way that they can be read on their own, depending on the reader’s area of interest, or read together to provide a comprehensive overview of the topic. Given its scope, the book will be of interest to practitioners, engineers and researchers seeking to leverage the latest advances in machine learning in order to develop solutions to practical problems in structural health monitoring, medical imaging, autonomous vehicles, wireless technology, and historical conservation.

Download or read book Advances in Deep Learning written by M. Arif Wani and published by Springer. This book was released on 2019-03-14 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces readers to both basic and advanced concepts in deep network models. It covers state-of-the-art deep architectures that many researchers are currently using to overcome the limitations of the traditional artificial neural networks. Various deep architecture models and their components are discussed in detail, and subsequently illustrated by algorithms and selected applications. In addition, the book explains in detail the transfer learning approach for faster training of deep models; the approach is also demonstrated on large volumes of fingerprint and face image datasets. In closing, it discusses the unique set of problems and challenges associated with these models.

Download or read book QSAR in Safety Evaluation and Risk Assessment written by Huixiao Hong and published by Elsevier. This book was released on 2023-08-12 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: QSAR in Safety Evaluation and Risk Assessment provides comprehensive coverage on QSAR methods, tools, data sources, and models focusing on applications in products safety evaluation and chemicals risk assessment. Organized into five parts, the book covers almost all aspects of QSAR modeling and application. Topics in the book include methods of QSAR, from both scientific and regulatory viewpoints; data sources available for facilitating QSAR models development; software tools for QSAR development; and QSAR models developed for assisting safety evaluation and risk assessment. Chapter contributors are authored by a lineup of active scientists in this field. The chapters not only provide professional level technical summarizations but also cover introductory descriptions for all aspects of QSAR for safety evaluation and risk assessment. Provides comprehensive content about the QSAR techniques and models in facilitating the safety evaluation of drugs and consumer products and risk assesment of environmental chemicals Includes some of the most cutting-edge methodologies such as deep learning and machine learning for QSAR Offers detailed procedures of modeling and provides examples of each model's application in real practice

Download or read book Handbook of Fingerprint Recognition written by Davide Maltoni and published by Springer. This book was released on 2009-08-29 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: A major new professional reference work on fingerprint security systems and technology from leading international researchers in the field. Handbook provides authoritative and comprehensive coverage of all major topics, concepts, and methods for fingerprint security systems. This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators.

Download or read book Biometric Recognition written by Zhenan Sun and published by Springer. This book was released on 2014-10-29 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th Chinese Conference on Biometric Recognition, CCBR 2014, held in Shenyang, China, in November 2014. The 60 revised full papers presented were carefully reviewed and selected from among 90 submissions. The papers focus on face, fingerprint and palmprint, vein biometrics, iris and ocular biometrics, behavioral biometrics, application and system of biometrics, multi-biometrics and information fusion, other biometric recognition and processing.