Multispectral Biometrics : Systems and Applications / / by David Zhang, Zhenhua Guo, Yazhuo Gong

• Record Nr.: UNINA9910254199603321
• Autore: Zhang David
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
• ISBN: 3-319-22485-9
• Edizione: [1st ed. 2016.]
• Descrizione fisica: 1 online resource (232 p.)
• Disciplina: 620
• Soggetti: Signal processing; Image processing; Speech processing systems; Biometrics (Biology); Biomedical engineering; Signal, Image and Speech Processing; Biometrics; Biomedical Engineering and Bioengineering
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references at the end of each chapters and index.
• Nota di contenuto: Multimodal 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.
• Sommario/riassunto: Describing 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’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.