Machine Learning for Biometrics

Machine Learning for Biometrics: Concepts, Algorithms and Applications highlights the fundamental concepts of machine learning, processing and analyzing data from biometrics and provides a review of intelligent and cognitive learning tools which can be adopted in this direction. Each chapter of the volume is supported by real-life case studies, illustrative examples and video demonstrations. The book elucidates various biometric concepts, algorithms and applications with machine intelligence solutions, providing guidance on best practices for new technologies such as e-health solutions, Data science, Cloud computing, and Internet of Things, etc.

In each section, different machine learning concepts and algorithms are used, such as different object detection techniques, image enhancement techniques, both global and local feature extraction techniques, and classifiers those are commonly used data science techniques. These biometrics techniques can be used as tools in Cloud computing, Mobile computing, IOT based applications, and e-health care systems for secure login, device access control, personal recognition and surveillance.

1. Fundamentals of Biometrics and reviews of different biometrics and multimodal biometrics
2. Detection techniques of different biometric traits
3. Preprocessing using Machine learning approaches
4. Feature extraction and selection using Machine learning approaches
5. Recognition (Verification and Identification) techniques
6. Behavioral biometrics
7. Biometrics in Forensic Identification
8. Biometric cryptography (Bio-Cryptography)
9. Multimodal Biometrics
10. Security Applications