000			03612nam a22004095i 4500
999			_c84844 _d84844
001			84844
003			ES-MaUEC
005			20240201145232.0
007			cr nn 008mamaa
008			150914s2016 gw a s 001 0 eng d
020			_a9783319224855
024	7		_a10.1007/978-3-319-22485-5 _2doi
040			_aES-MaUEC
050		4	_aTK7882.B56 _b2016 EB
082	0	4	_a621.382
100	1		_aZhang, David, _d1949- _0n 98076043 _948572
245	1	0	_aMultispectral Biometrics : _bSystems and Applications _cby David Zhang, Zhenhua Guo, Yazhuo Gong
250			_a1st ed.
264		1	_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XI, 229 p.) _b129 ilustraciones
336			_aTexto (visual) _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
505	0		_aMultimodal Fusion for Robust Identity Authentication: Role of Liveness Checks -- Multimodal Biometric Person Recognition System Based on Multi-Spectral Palmprint Features Using Fusion of Wavelet Representations -- Audio-Visual Biometrics and Forgery -- Face and ECG Based Multi-Modal Biometric Authentication -- Biometrical Fusion -- Input Statistical Distribution -- Normalization of Infrared Facial Images under Variant Ambient Temperatures -- Use of Spectral Biometrics for Aliveness Detection -- A Contactless Biometric System Using Palm Print and Palm Vein Features -- Liveness Detection in Biometrics -- Fingerprint Recognition -- A Gender Detection Approach -- Improving Iris Recognition Performance Using Quality Measures -- Application of LCS Algorithm to Authenticate Users within Their Mobile Phone Through In-Air Signatures -- Performance Comparison of Principal Component Analysis-Based Face Recognition in Color Space -- Block Coding Schemes Designed for Biometric Authentication -- Perceived Age Estimation from Face Images -- Cell Biometrics Based on Bio-Impedance Measurements -- Hand Biometrics in Mobile Dices.
520	3		_aDescribing several new biometric technologies, such as high-resolution fingerprint, finger-knuckle-print, multi-spectral backhand, 3D fingerprint, tongueprint, 3D ear, and multi-spectral iris recognition technologies, this book analyzes a number of efficient feature extraction, matching and fusion algorithms and how potential systems have been developed. Focusing on how to develop new biometric technologies based on the requirements of applications, and how to design efficient algorithms to deliver better performance, the work is based on the author{u2019}s research with experimental results under different challenging conditions described in the text. The book offers a valuable resource for researchers, professionals and postgraduate students working in the fields of computer vision, pattern recognition, biometrics, and security applications, amongst others.
650		7	_aIdentificación biométrica _2embne _9687509
700	1		_aGuo, Zhenhua _0n 85335103 _948574
700	1		_aGong, Yazhuo _0local _997353 _0Local
710	2		_aSpringerLink (Online service) _0Local _9106996
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-22485-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783319224855
907			_a.b12941220 _b04-11-17 _c21-11-16
942			_2lcc _cLE
945			_aTK7882.B56 Z43 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11585638 _z06-04-17
988			_aEBOOK, EBSPRINGER
998			_am _a_alco _a_vill _b04-11-17 _cm _dz _eo _feng _ggw _h0