| Document Type
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BL
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| Record Number
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864068
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| Main Entry
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Kumar, Ajay
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| Title & Author
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Contactless 3D fingerprint identification /\ Ajay Kumar.
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| Publication Statement
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Cham, Switzerland :: Springer,, 2018.
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| Series Statement
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Advances in computer vision and pattern recognition,
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| Page. NO
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1 online resource (x, 123 pages) :: illustrations (some color)
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| ISBN
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3319676814
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: 3319676822
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: 9783319676814
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: 9783319676821
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3319676806
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9783319676807
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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Intro; Preface; Contents; 1 Introduction to Trends in Fingerprint Identification; 1.1 Contact-Based Fingerprint Identification; 1.1.1 Matching Fingerprint Images; 1.2 Contactless 2D Fingerprint Identification; 1.3 Contactless 3D Fingerprint Identification; References; 2 3D Fingerprint Image Acquisition Methods; 2.1 Stereo Vision; 2.2 Patterned Lighting; 2.3 Optical Coherence Tomography; 2.4 Ultrasound Imaging; 2.5 Photometric Stereo; 2.6 Other Methods; References; 3 Contactless and Live 3D Fingerprint Imaging; 3.1 Contactless 3D Finger Image Acquisition Using Photometric Stereo.
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3.1.1 Imaging Setup and Calibration3.1.2 Preprocessing Acquired 2D Images; 3.1.3 Surface Normal and Albedo; 3.1.4 Generating 3D Fingerprint Images; 3.1.5 Removing Specular Reflection; 3.1.6 Addressing Non-Lambertian Influences During 3D Fingerprint Imaging; 3.2 Complexity for Online 3D Fingerprint Acquisition; References; 4 3D Fingerprint Acquisition Using Coloured Photometric Stereo; 4.1 Image Acquisition Setup for Coloured 3D Photometric Stereo; 4.2 Finger Motion Detection and Image Acquisition; 4.3 Reconstructing 3D Fingerprint Using RGB Channels.
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4.4 Reconstruction Accuracy and System Complexity4.5 Influence from Finger Skin Contamination; 4.6 Summary; References; 5 3D Fingerprint Image Preprocessing and Enhancement; 5.1 3D Fingerprint Data Format and Representation; 5.2 Contactless 3D Fingerprint Image Enhancement; 5.3 Estimating 3D Fingerprint Surface Curvature; 5.4 Contactless Fingerprint Image Preprocessing; References; 6 Representation, Recovery and Matching of 3D Minutiae Template; 6.1 Conventional 2D Fingerprint Minutiae Representation; 6.2 Minutiae Representation in 3D Space.
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6.3 Recovering Minutiae in 3D Space from the 3D Fingerprint Images6.4 Matching 3D Minutiae Templates; 6.4.1 3D Minutiae Quality; 6.4.2 3D Minutiae Selection; 6.5 Development of Unified Distance for 3D Minutiae Matching; 6.6 Performance Evaluation; 6.7 Summary and Conclusions; References; 7 Other Methods for 3D Fingerprint Matching; 7.1 Fast 3D Fingerprint Matching Using Finger Surface Code; 7.2 Tetrahedron-Based 3D Fingerprint Matching; 7.2.1 3D Minutiae Hierarchical Tetrahedron Matching; 7.3 3D Fingerprint Matching Using Surface Normals; 7.4 Summary and Conclusions; References.
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8 Individuality of 3D Fingerprints8.1 Probability of False Random Correspondence Between Two 3D Fingerprints; 8.1.1 Relative Improvement from 3D Fingerprint Individuality; 8.2 Probability of False Random Correspondence Using Noisy Minutiae Matching; References; Index.
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| Abstract
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This important text/reference presents the first dedicated review of techniques for contactless 3D fingerprint identification, including novel and previously unpublished research. The text provides a systematic introduction to 3D fingerprint identification, covering the latest advancements in contactless 2D and 3D sensing technologies, and detailed discussions on each key aspect in the development of an effective 3D fingerprint identification system. Topics and features: Introduces the key concepts and trends in the acquisition and identification of fingerprint images, and a range of 3D fingerprint imaging techniques Proposes a low-cost method for online 3D fingerprint image acquisition, and an efficient 3D fingerprint imaging approach using coloured photometric stereo Describes pre-processing operations on point cloud 3D fingerprint data, and explains the specialized operations for reconstructing 3D fingerprints from live finger scans Examines the representation of minutiae in 3D space, providing details on recovering these features from point cloud data, and on matching such 3D minutiae templates Reviews various 3D fingerprint matching methods, including binary surface code-based approaches and a tetrahedron-based matching approach Discusses the uniqueness of 3D fingerprints, evaluating the benefits of employing 3D fingerprint identification over conventional 2D fingerprint techniques This unique work is a must-read for all researchers seeking to make further advances in this area, towards the exciting opportunities afforded by contactless 3D fingerprint identification for improving the hygiene, user convenience, and matching accuracy of fingerprint biometric technologies. Dr. Ajay Kumar is an Associate Professor in the Department of Computing at the Hong Kong Polytechnic University. He has previously served as an Assistant Professor at the Department of Electrical Engineering, IIT Delhi. He is a Fellow of IEEE and IAPR. His other publications include the Springer title Deep Learning for Biometrics.
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| Subject
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Fingerprints-- Identification-- Technological innovations.
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Artificial intelligence.
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Artificial intelligence.
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COMPUTERS-- General.
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Computers-- Law and legislation.
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Engineering.
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Legal aspects of IT.
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| Subject
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Pattern recognition.
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| Dewey Classification
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006.2/483998
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| LC Classification
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GN192
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