**Preface to "Biometric Systems"**

Biometric recognition/verification continues to be one of the most widely studied pattern recognition problems. The field is being driven in large part by the recent rise in sophisticated nation-state hacking and the increasing need of advancing technological systems, such as the Internet and cellular phones, to secure personal identification. Rapidly fading are the days of password protection. Biometrics along with authenticator apps and multifactor authentication are being pushed to safeguard systems in the new threat environment by many industrial leaders, such as Microsoft.

Biometric recognition is defined by several critical issues involved in the problem, such as quality checking of sensor inputs, biodata security, aliveness detection, and multimodal authentication. Regardless of the biometric chosen, all recognition systems must also isolate and extract a set of features in the biometric image or pattern that offers the greatest amount of information, whether these features are engineered or automatically determined by the classifier system.

This book's chapters present the very best work in biometric recognition and verification. Topics run the gamut of research in this field: security issues, signature verification (online and on mobile touch-screens), fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition systems), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems, including coverage of the latest equipment for multi-modal contactless verification, the fusion of fingerprint identification with either finger-vein and finger knuckle-print identification or ECT signals or hand vein recognition. A chapter is also dedicated to image quality as it affects performance in biometric systems based on images. Many chapters propose novel methods for biometric recognition and verification, including the introduction of new descriptors and feature sets, the addition of depth information and augmentation, and the application in this field of the latest deep learner architectures. In several chapters, algorithms are exhaustively compared and verified across many data sets.

Due to the accelerating progress in biometrics research, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting state of the art in biometrics research, covering essential topics in the contemporary scene. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study.

> **Loris Nanni, Sheryl Brahnam** *Editors*
