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Record Nr. |
UNINA9910299918303321 |
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Autore |
Zhang David |
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Titolo |
Advanced Biometrics / / by David Zhang, Guangming Lu, Lei Zhang |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
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ISBN |
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Edizione |
[1st ed. 2018.] |
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Descrizione fisica |
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1 online resource (336 pages) : illustrations |
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Disciplina |
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Soggetti |
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Signal processing |
Image processing |
Speech processing systems |
Biometrics (Biology) |
Biomedical engineering |
Signal, Image and Speech Processing |
Biometrics |
Biomedical Engineering and Bioengineering |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters and index. |
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Nota di contenuto |
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OVERVIEW -- High Resolution Partial Fingerprint Alignment using Pore-Valley Descriptors -- Adaptive Fingerprint Pore Modeling and Extraction -- A Reference High Resolution using Minutiae and Pores -- Online Finger-Knuckle-Print Verification for Personal Authentication -- Phase Congruency Induced Local Features for FKP Verification -- Ensemble of Local and Global Information for Finger-Knuckle-Print Verification -- Reconstruction based FKP Verification with Score Level Adaptive Binary Fusion -- 3D Fingerprint Reconstruction and Recognition -- Multi-Spectral Backhand Authentication. |
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Sommario/riassunto |
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This book describes a range of new biometric technologies, such as high-resolution fingerprint, finger-knuckle-print, multi-spectral backhand, 3D fingerprint, tongueprint, 3D ear, and multi-spectral iris technologies. Further, it introduces readers to efficient feature extraction, matching and fusion algorithms, in addition to developing potential systems of its own. These advanced biometric technologies |
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and methods are divided as follows: 1. High-Resolution Fingerprint Recognition; 2. Finger-Knuckle-Print Verification; 3. Other Hand-Based Biometrics; and 4. New Head-Based Biometrics. Traditional biometric technologies, such as fingerprint, face, iris, and palmprint, have been extensively studied and addressed in many research books. However, all of these technologies have their own advantages and disadvantages, and there is no single type of biometric technology that can be used for all applications. Many new biometric technologies have been developed in r ecent years, especially in response to new applications. The contributions gathered here focus on how to develop a new biometric technology based on the requirements of essential applications, and how to design efficient algorithms that yield better performance. |
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