主要介绍指纹识别，一本比较好的指纹指纹识别的书籍，值得一看Second editionSpringerDavide maltoniDario maioBiometric Systems Lab DEis)Biometric Systems Lab DEIs)Universita di bolognaUniversita di bolognaⅤ ia sacchi.3Ⅴ ia sacchi.347023 Cesena. Ital47023 Cesena. Italmaltoni(@csr. uniboitdmaic(@deis. uniboitAnil K. jainSalil PrabhakarDepartment of Computer ScienceDigitalPersona, IncMichigan State Universit720 Bay Road3115, Engineering BuildingRedwood City CA 94063, USAEast Lansing MI 48823, USAsalilpadigitalpersona.comjain (@cse. msu. eduISBN:978-1-84882-253-5e-ISBN:978-1-84882-254-2British library cataloguing in Publication DataA catalogue record for this book is available from the British LibraryLibrary of Congress Control Number: 2009926293C Springer-Verlag London Limited 2009Apart from any fair dealing for the purposes of research or private study, or criticism or review, aspermitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing ofthe publishers, or in the case of reprographic reproduction in accordance with the terms of licensesissued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those termsshould be sent to the publishersThe use of registered names, trademarks, etc, in this publication does not imply, even in theabsence of a specific statement, that such names are exempt from the relevant laws and regulationsand therefore free for general useThe publisher makes no representation, express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors oromissions that may be madePrinted on acid-free paperSpringer Science+ Business Mediaspringer. comContentsPrefaceOObjectiveXOrganization and featuresX11From the first to the second editits of the dvdIntended AudieAcknowledgments……1 Introduction .mm1.1 Introduction1.2 Biometric Recognition....….….…….……………………1.3 Biometric S ystems1. 4 Comparison of traits1.5 System errors1. 5. 1 Reasons behind system errors121.5.2 Capture module errors………131. 5. 3 Feature extraction module errors141.5.4 Template creation module errors141.5.5 Matching module errors141.5.6 Verification error rates161.5.7 Identification error rates201.6 System Evaluation221.7 Applications of Fingerprint Systems1.7.1 Application characteristics7.2 Application categories1.7.3 Barriers to adoption.301. 8 History of Fingerprints1.9 Formation of Fingerprints.341.10 Individuality of Fingerprints………………351.11 Fingerprint Sensing and Storage361. 12 Fingerprint Representation and Feature Extraction381.13 Fingerprint Matching411. 14 Fingerprint Classification and Indexing1.15 Synthetic Fingerprints………451.16 Biometric fusion45Contents1. 17 System Integration and Administration Issues1.18 Securing Fingerprint Systems501. 19 Privacy Issues511.20 Summary and Future Prospects1. 21 Image Processing and Pattern Recognition Background.......1.21. 1 Image processing books3551.2 1.2 Pattern recognition books1. 21. 3 Journals562 Fingerprint Sensing…............…………鲁。。。。。。春鲁非非2.1 Introduction非非非非非非72.2 Off-Line Fingerprint acquisition612.3 Live-Scan Fingerprint Sensin2.3. 1 Optical sensors2.3.2 Solid-state sensors.672. 3. 3 Ultrasound sensors2. 4 Touch Versus Sweep702. 4. 1 Image reconstruction from slices........................722.5 Fingerprint Images and Their Parameters…………….….…………………1722.6 Image Quality Specifications for Fingerprint Scanners.,772.7 Operational Quality of Fingerprint Scanners.782.8 Examples of Fingerprint Scanners..2.9 Dealing with Small Area Sensors.....……892.10 Storing and Compressing Fingerprint Images.……….…….922.11 Summary953 Fingerprint Analysis and representation………………,…,….….…………973.1 Introduction973.2 Local Ridge Orientation1023.2. 1 Gradient-based approaches1033.2.2 Slit-and projection-based approaches1063.2. 3 Orientation estimation in the frdomain1073.2.4 Other approaches1083.2.5 Orientation image regularization1083.2.6 Global models of ridge orientations1103.3 Local Ridge Frequencyl123.4 Segmentation.…1163.5 Singularity and Core Detection...….…….….…….1203.5.1 Poincare index1203.5.2 Methods based on local characteristics of the orientation image.1243.5.3 Partitioning-based methods......1253.5.4 Methods based on a global model of the orientation image........ 126Contents vii3.5.5 Core detection and registration1283.5.6 Miscell1303.6 Enhancement1313.6. 1 Pixel-wise enhancement1333.6.2 Contextual filtering.........1343.6.3 Multi-resolution enhancement1413.6.4 Crease detection and removal1413.6.5 Miscellanea.1433.7 Minutiae detection1433.7.1 Binarization-based methods1433.7.2 Direct gray-scale extraction.1513.7.3 Minutiae encoding standards553.8 Minutiae Filtering.………1573.8. 1 Structural post-processin1573.8.2 Minutiae filtering in the gray-scale domain1593.9 Estimation of Ridge count1613.10 Estimation of Fingerprint Quality3.10. 1 Global quality estimation1633.10.2 Local quality estimation1653.11 Summary…………1654 Fingerprint Matching……………………….1674.1 Introduction1674.2 Correlation- Based Techniques........………1724. 3 Minutiae-Based Methods1774.3. 1 Problem formulation1774.3.2 Similarity score184.3.3 Point pattern matching4.3. 4 Some simple algebraic geometry methodsl811834.3. 5 Hough transform-based approaches for minutiae matching......... 1844.3.6 Minutiae matching with pre-alignment.1884.3. 7 Avoiding alis1924.3.8 Miscellanea.1944.4 Global Versus Local Minutiae Matching………1954.4.1 The earlier ar4.4.2 Local structure matching through invariant distances and angles.1964.4.3 Evolution of local structure matching1984.4.4 Consolidation.20244.5 Asymmetrical local matching………4.5 Dealing with Distortion.……4.5. 1 Tolerance boxes207tents4.5.2 Warping…2084.5.3 Multiple- registration and clustering…………2104.5.4 Triangulation and incremental expansion2114.5.5 Normalization2124.5.6 Fingerprint distortion models2134.6 Non-Minutiae Feature-Based Matching techniques2164.6.1 Global and local texture information2174.6.2 Geometrical attributes and spatial relationship of the ridge lines…………2214.6.3 Level 3 features224.7 Comparing the Performance of Matching Algorithms…………4.7. 1 Fingerprint database2254.7.2 Fingerprint evaluation campaigns.284.7.3 Interoperability of fingerprint recognition algorithms2284.7.4 Further notes on performance evaluation.2314.8 Summary2325 Fingerprint Classification and Indexing….....……2355.1 Introduction2355.2 Classification Techniques2385.2. I Rule- based approaches.……….2425.2.2 Syntactic approaches……….2445.2.3 Structural approaches...……………….2455.2.4 Statistical approaches2465.2.5 Neural network-based approaches.2495.2.6 Multiple classifier-based approaches.2505.2. 7 Miscellanea2535.3 Performance of Fingerprint Classification Techniques………2535.3. 1 Results on nist db425553 2 Results on nist db142554 Fingerprint Indexing and Retrieval.2585.4.1 Fingerprint sub-classification2585.4.2 Continuous classification and other indexing techniques.2595.4.3 Retrieval strategies2635.4.4 Performance of fingerprint retrieval techniques2655.5 Summary2686 Synthetic Fingerprint Generation………………………………2716.1 Introduction2716.2 Background2726. 3 The SFinge method2746.4 Generation of a Master Fingerprint2776. 4.1 Fingerprint area generationContents6.4.2 Orientation image generation2786.4.3 Frequency image generation2826.4.4 Ridge pattern generation.286.5 Generation of Synthetic Fingerprint Impressions………………2856.5.1 ariation in ridge thickness……6.5.2 Fingerprint distortion2886.5.3 Perturbation and global translation/rotation.2906.5.4 Background generation.………06.6 Validation of the Synthetic Generator……2936.7 Automatic Generation of Ground Truth features2976.8 SFinge software tool,非2976.9 Summary….3017 Biometric fusion∴.3037. 1 Introduction7.2 Performance Improvement from Fusion3067.3 Application-specific Considerations3087. 4 Sou3107.4.1 Fusion of multiple traits3127.4.2 Multi-finger fu3157.4.3 Fusion of multiple samples of a finger: different sensors……….3157.4.4 Fusion of multiple samples of a finger: same sensor………….3167.4.5 Fusion of multiple representation and matching algorithms…………….3177.5 Level of detail of Information in Fusion........................3187.6 Image-Level Fusion3207.7 Feature-Level Fusion7. 8 Rank-Level fusion3247. 9 Score-Level Fusion3257.9.1 Score normalization methods3267.9.2 Bayesian framework for score fusion.3297.9.3 Density-based methods.3337. 9. 4 Classifier-based methods.3347. 10 Decision-Level Fusion3377.11 Summary3388 Fingerprint Individuality……………………………………………3418.1 Introduction.……………418.3 Uniform Minutiae Placement m………8.2 Background.3448. 3. 1 The model8.3.2 Parameter estimation. .....................................................................................3568.3.3 Experimental evaluation····.359Contents8.4 Finite mixture minutiae placement model∴3648. 4. 1 The model3648.4.2 Model fitting.3668.4.3 Experimental evaluation.…….3688.5 Other recent Approaches.8.6 Summary.3699 Securing Fingerprint Systems………….,….,……….………………………………3719. 1 Introduction9. 2 Types of Failures in Fingerprint Systems3749.3 Methods of Obtaining Fingerprint Data and Countermeasures∴.3769.3. 1 Obtaining fingerprint data of a specific user.3769.3.2 Obtaining generic fingerprint data3799. 4 Methods of Injecting Fingerprint Data and Countermeasures3809.4.1 Injecting a fake finger at the scanner3829. 4.2 Injecting fingerprint in a communication channel or in the template storage 3839.4.3 Replacing a system module with malicious software3859.5 Liveness Detection Techniques....................................3869.5. I Finger skin properties and finger vitality signs…………………3869.5.2 Effectiveness of liveness detection techniques3919.6 Building a Closed Fingerprint System9.6. 1 Match-on-card techniques..........3939.6.2 Systen-on- device and systen-on-a- chip techniques……………3969.6.3 Mutual and distributed trust techniques. ................................................3979.7 Template protection techniques3989.7.1 Non-invertible trans forms4039.7.2 Salting…4079.7.3Key- generation biometric cryptosystems………4079.7.4 Key-binding biometric cryptosystems4109. 8 Summary416Bibliography………………,,…….…….………4l7Indexe。。。。。483