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008			161227s2017 sz o 001 0 eng d
020			_a3319473018 _q(electronic bk.)
020			_a9783319473017 _q(electronic bk.)
020			_z331947300X
020			_z9783319473000
035			_a(OCoLC)967264255 _z(OCoLC)967326040 _z(OCoLC)970386521 _z(OCoLC)970614758 _z(OCoLC)970682310 _z(OCoLC)971209516 _z(OCoLC)971585734 _z(OCoLC)972433783 _z(OCoLC)972619113 _z(OCoLC)972780296 _z(OCoLC)974649564 _z(OCoLC)981034030 _z(OCoLC)1005779391 _z(OCoLC)1011849316
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050		4	_aTK7882.B56 _bB566 2017 EB
245	0	0	_aBiometric security and privacy : _bopportunities & challenges in the big data era _cRichard Jiang, Somaya Al-maadeed, Ahmed Bouridane, Prof. Danny Crookes, Azeddine Beghdadi, editors.
264		1	_aCham, Switzerland _bSpringer _c2017
300			_a1 recurso en línea
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	0		_aSignal processing for security technologies
500			_aIncluye índice
500			_aSpringerLink
505	0		_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.
505	8		_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.
505	8		_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.
505	8		_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.
505	8		_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.
520	3		_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.
988			_aEBOOK, asignarmaterias, EBSPRINGER_2017B
650		7	_aIdentificación biométrica _2embne _0(OCoLC)fst00817247 _9687509
700	1		_aAl-madeed, Somaya, _eeditor literario
700	1		_aBeghdadi, A. _q(Azeddine), _eeditor literario
700	1		_aBouridane, Ahmed, _eeditor literario
700	1		_aCrookes, Danny, _d1956- _eeditor literario
700	1		_aJiang, Richard, _eeditor literario
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=http://link.springer.com/10.1007/978-3-319-47301-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cM1S
998			_b02/2018 _dz _e- _zSI