1.

Record Nr.

UNINA9910299713203321

Titolo

Signal and image processing for biometrics / / Jacob Scharcanski, Hugo Proença, Eliza Du, editors

Pubbl/distr/stampa

Berlin : , : Springer, , [2014]

©2014

ISBN

3-642-54080-5

Descrizione fisica

1 online resource (336 pages) : illustrations

Collana

Lecture notes in electrical engineering, , 1876-1119 ; ; volume 292

Disciplina

006.37

570.1/5195

Soggetti

Signal processing

Image processing

Speech processing systems

Biometrics (Biology)

System safety

Signal, Image and Speech Processing

Biometrics

Security Science and Technology

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.

Nota di contenuto

Data and Information Dimensionality in Non-Cooperative Face Recognition -- Remote Identification of Faces -- Recognizing Altered Facial Appearances Due to Aging and Disguise -- Using Score Fusion for Improving the Performance of Multispectral Face Recognition -- Unconstrained ear processing -- Feature Quality-based Unconstrained Eye Recognition -- Speed-invariant Gait Recognition -- Quality Induced Multi classifier Fingerprint Verification using Extended Feature Set -- Quality Measures for Online Handwritten Signatures -- Human tracking in non-cooperative scenarios.

Sommario/riassunto

This volume offers a guide to the state of the art in the fast evolving field of biometric recognition to newcomers and experienced practitioners. It is focused on the emerging strategies to perform biometric recognition under uncontrolled data acquisition conditions.



The mainstream research work in this field is presented in an organized manner, so the reader can easily follow the trends that best suits her/his interests in this growing field. The book chapters cover the recent advances in less controlled / covert data acquisition frameworks, segmentation of poor quality biometric data, biometric data quality assessment, normalization of poor quality biometric data. contactless biometric recognition strategies, biometric recognition robustness, data resolution, illumination, distance, pose, motion, occlusions, multispectral biometric recognition, multimodal biometrics, fusion at different levels, high confidence automatic surveillance.