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000778632 0247_ $$a10.1007/978-3-319-47301-7$$2doi
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000778632 24500 $$aBiometric security and privacy :$$bopportunities & challenges in the big data era /$$cRichard Jiang, Somaya Al-maadeed, Ahmed Bouridane, Prof. Danny Crookes, Azeddine Beghdadi, editors.
000778632 260__ $$aCham, Switzerland :$$bSpringer,$$c2017.
000778632 300__ $$a1 online resource.
000778632 336__ $$atext$$btxt$$2rdacontent
000778632 337__ $$acomputer$$bc$$2rdamedia
000778632 338__ $$aonline resource$$bcr$$2rdacarrier
000778632 347__ $$atext file$$bPDF$$2rda
000778632 4901_ $$aSignal processing for security technologies
000778632 500__ $$aIncludes index.
000778632 5050_ $$aPreface; Contents; 1 Fingerprint Quality Assessment: Matching Performance and Image Quality; 1.1 Introduction; 1.2 Background; 1.3 Trial Measures; 1.3.1 Metrics with Single Feature; 1.3.2 Segmentation-Based Metrics; 1.3.2.1 FQA via Informative Region; 1.3.2.2 FQA via Pixel-Pruning; 1.3.3 FQA via Multi-feature; 1.4 Experimental Results; 1.4.1 Software; 1.4.2 Database et Protocol; 1.4.3 Results; 1.4.3.1 ES with Quality; 1.4.3.2 Isometric Bins; 1.4.4 Discussion via Sample Utility; 1.5 Conclusion; References.
000778632 5058_ $$a2 A Novel Perspective on Hand Vein Patterns for Biometric Recognition: Problems, Challenges, and Implementations2.1 Introduction; 2.2 Vein Pattern Scanning Using Optical Methods; 2.2.1 Vein Pattern Visualization; 2.2.2 Structure of a Hand Vein Recognition Device; 2.3 Problems and Challenges in Vein Pattern Applications; 2.4 Modern Perspectives on Vein Structure Recognition; 2.4.1 Ergonomics and Hand Pose Assessment in Vein pattern Identification; 2.4.2 Synthetic Vein Pattern Generation; 2.4.3 Vein Biometrics in a Connected World; 2.5 Conclusions; References.
000778632 5058_ $$a3 Improving Biometric Identification Performance Using PCANet Deep Learning and Multispectral Palmprint3.1 Introduction; 3.2 Image Features; 3.3 Proposed Methodology; 3.3.1 Feature Extraction; 3.3.1.1 PCANet Deep Learning; 3.3.1.2 Flexibility Property; 3.3.2 Classification; 3.4 Experimental Results and Discussion; 3.4.1 Experimental Databases; 3.4.2 Identification Test Results; 3.4.2.1 Performance of the Unimodal Systems; 3.4.2.2 Performance of the Multimodal Systems; 3.4.3 Comparison Study; 3.5 Conclusion and Further Work; References; 4 Biometric Acoustic Ear Recognition; 4.1 Introduction.
000778632 5058_ $$a4.2 Ear Biometrics and Acoustics4.2.1 The Ear as a Biometric; 4.2.2 Image Based Ear Recognition; 4.2.3 Acoustic Based Ear Recognition; 4.2.4 Acoustic Properties of The Ear; 4.2.5 Ears Coupled to Headphones; 4.3 Measuring Device; 4.4 Experiments; 4.4.1 Design Considerations; 4.4.2 Data Collection; 4.5 Data Analysis; 4.5.1 Preprocessing; 4.5.2 Initial Data Analysis; 4.5.3 Statistical Attributes; 4.5.4 Feature Selection and Extraction; 4.5.4.1 All Frequency Components; 4.5.4.2 Octave Bands; 4.5.4.3 Acoustic Properties of The Outer Ear; 4.6 Results; 4.6.1 Performance of All Frequency Components.
000778632 5058_ $$a4.6.2 Performance of PCA4.6.3 Performance of Octave Bands; 4.6.4 Performance of Ear Characteristic Bands and Peaks; 4.7 Discussion and Future Work; 4.8 Conclusion; References; 5 Eye Blinking EOG Signals as Biometrics; 5.1 Introduction; 5.2 Origin of Eye Blinking EOG Signals; 5.3 Proposed Approach for Eye Blinking EOG Biometric System; 5.3.1 Data Acquisition; 5.3.2 Pre-processing; 5.3.3 Feature Extraction; 5.3.4 Feature Selection; 5.3.5 Classification; 5.3.5.1 Linear Decision Rule; 5.3.5.2 Mahalanobis Decision Rule; 5.4 Experimental Setup and Results; 5.4.1 Identification Mode.
000778632 506__ $$aAccess limited to authorized users.
000778632 520__ $$aThis book highlights recent research advances on biometrics using new methods such as deep learning, nonlinear graph embedding, fuzzy approaches, and ensemble learning. Included are special biometric technologies related to privacy and security issues, such as quality issue, biometric template protection, and anti-spoofing. The book also focuses on several emerging topics such as big data issues, mobile biometrics and multispectral biometrics, and includes a number of new biometrics such as vein pattern, acoustic biometrics, eye-blinking EOG, ECG, gait and handwriting. Authors also show how to use biometrics in cyber security applications and its relevant legal matters under EU legislation. The contributors cover the topics, their methods, and their applications in depth.
000778632 650_0 $$aBiometric identification.
000778632 650_0 $$aBig data.
000778632 650_0 $$aArtificial intelligence.
000778632 7001_ $$aJiang, Richard,$$eeditor.
000778632 7001_ $$aAl-madeed, Somaya,$$eeditor.
000778632 7001_ $$aBouridane, Ahmed,$$eeditor.
000778632 7001_ $$aCrookes, Danny,$$d1956-$$eeditor.
000778632 7001_ $$aBeghdadi, A.$$q(Azeddine),$$eeditor.
000778632 77608 $$iPrint version:$$z9783319473000$$z331947300X$$w(OCoLC)958460434
000778632 830_0 $$aSignal processing for security technologies.
000778632 852__ $$bebk
000778632 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-47301-7$$zOnline Access$$91397441.1
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000778632 980__ $$aEBOOK
000778632 980__ $$aBIB
000778632 982__ $$aEbook
000778632 983__ $$aOnline
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