Signal and Image Processing for Biometrics [electronic resource] / edited by Jacob Scharcanski, Hugo Proença, Eliza Du.

By: Scharcanski, Jacob [editor.]Contributor(s): Proença, Hugo [editor.] | Du, Eliza [editor.] | SpringerLink (Online service)Material type: TextTextLanguage: English Series: Lecture Notes in Electrical Engineering: 292Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014Description: X, 331 p. 150 illus., 91 illus. in color. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783642540806Subject(s): Engineering | Biometrics | Engineering | Signal, Image and Speech Processing | Biometrics | Security Science and TechnologyAdditional physical formats: Printed edition:: No titleDDC classification: 621.382 LOC classification: TK5102.9TA1637-1638TK7882.S65Online resources: Click here to access online
Contents:
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.
In: Springer eBooksSummary: 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.
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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.

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.

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