Handbook of biometrics for forensic science /

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Bibliographic Details
Imprint:Cham, Switzerland : Springer, 2017.
Description:1 online resource
Language:English
Series:Advances in computer vision and pattern recognition, 2191-6586
Advances in computer vision and pattern recognition.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11271240
Hidden Bibliographic Details
Other authors / contributors:Tistarelli, Massimo, 1962- editor.
Champod, Christophe, editor.
ISBN:9783319506739
3319506730
9783319506715
3319506714
Digital file characteristics:text file PDF
Notes:Includes index.
Includes bibliographical references at the end of each chapters and index.
Online resource; title from PDF title page (SpringerLink, viewed February 10, 2017).
Summary:This comprehensive handbook addresses the sophisticated forensic threats and challenges that have arisen in the modern digital age, and reviews the new computing solutions that have been proposed to tackle them. These include identity-related scenarios which cannot be solved with traditional approaches, such as attacks on security systems and the identification of abnormal/dangerous behaviors from remote cameras, for which advanced identification technologies and pattern recognition algorithms can offer novel ways to provide proof of identity. Topics and features: Presents the first dedicated volume on biometrics for forensic science and criminal investigations Contains contributions from an international selection of preeminent authorities, including members of the EU COST Action "Biometrics and Forensics for the Digital Age" Provides an in-depth analysis of the state of the art, together with a broad review of the available technologies and their potential applications Discusses potential future developments in the adoption of advanced technologies for the automated or semi-automated analysis of forensic traces Presents a particular focus on the acquisition and processing of data from real-world forensic cases Offers an holistic perspective, integrating work from different research institutions and combining viewpoints from both biometric technologies and forensic science This innovative volume will inspire and inform professionals, young researchers and graduate students interested in the use of cutting-edge biometric technologies in the service of criminal investigations. Dr. Massimo Tistarelli is a Professor of Computer Science in the Department of Communication Science and Information Technology at the University of Sassari. Dr. Christophe Champod is a Professor of Forensic Science in the School of Criminal Justice at the University of Lausanne.
Other form:Print version: Handbook of biometrics for forensic science. Cham, Switzerland : Springer, 2017 3319506714 9783319506715
Standard no.:10.1007/978-3-319-50673-9

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245 0 0 |a Handbook of biometrics for forensic science /  |c Massimo Tistarelli, Christophe Champod, editors. 
264 1 |a Cham, Switzerland :  |b Springer,  |c 2017. 
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500 |a Includes index. 
588 0 |a Online resource; title from PDF title page (SpringerLink, viewed February 10, 2017). 
505 0 |a Preface; Contents; 1 Biometric Technologies for Forensic Science and Policing: State of the Art; Abstract; 1.1 A Short Historical Introduction and Forensic Context; 1.2 Recent Developments of Biometric Technologies in Forensic Science; 1.3 Challenges; 1.4 Conclusions; Acknowledgements; References; Analysis of Fingerprints and Fingermarks; 2 Capture and Analysis of Latent Marks; Abstract; 2.1 Introduction; 2.2 Fingerprint Characteristics; 2.3 Conventional Latent Mark Acquisition Techniques; 2.4 Contact-Less Latent Mark Acquisition Techniques; 2.5 Latent Mark Analysis Process. 
505 8 |a 2.6 Legal Challenges of Applying New Techniques in the Latent Mark Processing2.7 Summary; References; 3 Automated Fingerprint Identification Systems: From Fingerprints to Fingermarks; Abstract; 3.1 Introduction; 3.1.1 History; 3.1.2 AFIS Functionalities; 3.1.3 Fingerprint Identification Accuracy; 3.2 Automated Fingerprint/Mark Technology; 3.2.1 Fingerprints; 3.2.2 Fingermarks; 3.3 Segmentation; 3.4 Enhancement; 3.5 Forensic Applications; 3.5.1 Applications Using fingerprints; 3.5.1.1 Identity Management Within Criminal Justice Systems; 3.5.1.2 Forensic Identification of Missing Persons. 
505 8 |a 3.5.2 Application Using Fingermarks3.5.2.1 Forensic Intelligence; 3.5.2.2 Forensic Investigation; 3.5.2.3 Forensic Evaluation; 3.5.3 Current Challenges; 3.5.3.1 Automation and Transparency; 3.5.3.2 Scalability and Interoperability; 3.5.3.3 Forensic Fingermark Processes; 3.6 Conclusion; References; 4 Challenges for Fingerprint Recognition-Spoofing, Skin Diseases, and Environmental Effects; Abstract; 4.1 Spoofing and Anti-spoofing; 4.1.1 Perspiration; 4.1.2 Spectroscopic Characteristics; 4.1.3 Ultrasonic Technology; 4.1.4 Physical Characteristics: Temperature. 
505 8 |a 4.1.5 Physical Characteristics: Hot and Cold Stimulus4.1.6 Physical Characteristics: Pressure Stimulus; 4.1.7 Physical Characteristics: Electrical Properties; 4.1.8 Physical Characteristics: Pulse; 4.1.9 Physiological Basics of Heart Activity; 4.1.10 Physical Characteristics: Blood Oxygenation; 4.1.11 Fingerprint Spoof Preparation; 4.2 Skin Diseases; 4.3 Environmental Distortions; 4.3.1 Phenomena Influencing Fingerprint Acquisition; 4.3.2 Methods for Generation of Synthetic Fingerprints; 4.4 Conclusion; Acknowledgments; References; 5 Altered Fingerprint Detection; 5.1 Introduction. 
505 8 |a 5.2 Background of Fingerprint Alterations5.2.1 Obliteration; 5.2.2 Distortion; 5.2.3 Imitation; 5.3 Related Work; 5.3.1 Orientation Field Analysis; 5.3.2 Minutiae Distribution Analysis; 5.4 Recent Algorithms for Fingerprint Alteration Detection; 5.4.1 Preprocessing; 5.4.2 Singular Point Density Analysis; 5.4.3 Minutia Orientation Analysis; 5.4.4 Orientation Difference Map; 5.4.5 Orientation Density Map; 5.5 Evaluation and Results; 5.6 Conclusion; References; Face and Video Analysis; 6 Face Sketch Recognition via Data-Driven Synthesis; 6.1 Introduction; 6.2 Related Work. 
520 |a This comprehensive handbook addresses the sophisticated forensic threats and challenges that have arisen in the modern digital age, and reviews the new computing solutions that have been proposed to tackle them. These include identity-related scenarios which cannot be solved with traditional approaches, such as attacks on security systems and the identification of abnormal/dangerous behaviors from remote cameras, for which advanced identification technologies and pattern recognition algorithms can offer novel ways to provide proof of identity. Topics and features: Presents the first dedicated volume on biometrics for forensic science and criminal investigations Contains contributions from an international selection of preeminent authorities, including members of the EU COST Action "Biometrics and Forensics for the Digital Age" Provides an in-depth analysis of the state of the art, together with a broad review of the available technologies and their potential applications Discusses potential future developments in the adoption of advanced technologies for the automated or semi-automated analysis of forensic traces Presents a particular focus on the acquisition and processing of data from real-world forensic cases Offers an holistic perspective, integrating work from different research institutions and combining viewpoints from both biometric technologies and forensic science This innovative volume will inspire and inform professionals, young researchers and graduate students interested in the use of cutting-edge biometric technologies in the service of criminal investigations. Dr. Massimo Tistarelli is a Professor of Computer Science in the Department of Communication Science and Information Technology at the University of Sassari. Dr. Christophe Champod is a Professor of Forensic Science in the School of Criminal Justice at the University of Lausanne. 
504 |a Includes bibliographical references at the end of each chapters and index. 
650 0 |a Biometric identification  |v Handbooks, manuals, etc. 
650 0 |a Forensic sciences  |v Handbooks, manuals, etc. 
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650 7 |a Pattern recognition.  |2 bicssc 
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