Advanced biometrics by Zhang, David, Lu, Guangming; Zhang, Lei instant download
1 online resource (xiii, 335 pages), 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 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, Print version record, Preface; Contents; Chapter 1: Overview; 1.1 Why Biometrics; 1.2 History of Biometrics; 1.3 Biometrics Systems; 1.4 Recent Biometrics Development; 1.4.1 Multi-biometrics; 1.4.2 3D Biometrics; 1.4.3 Multispectral Biometrics; 1.5 Arrangement of This Book; References; Part I: High Resolution Fingerprint Recognition; Chapter 2: High Resolution Partial Fingerprint Alignment; 2.1 Introduction; 2.1.1 High Resolution Partial Fingerprint; 2.1.2 Fingerprint Alignment; 2.1.3 Partial Fingerprint Alignment Based on Pores; 2.2 Feature Extraction; 2.2.1 Ridge and Valley Extraction; 2.2.2 Pore Extraction, 2.2.3 Pore-Valley Descriptors2.3 PVD-Based Partial Fingerprint Alignment; 2.4 Experiments; 2.4.1 The Dataset;
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