Face Recognition Across the Imaging Spectrum

This authoritative text/reference presents a
comprehensive review of algorithms and techniques for face recognition (FR),
with an emphasis on systems that can be reliably used in operational
environments. Insights are provided by an international team of pre-eminent
experts into the processing of multispectral and hyperspectral face images
captured under uncontrolled environments. These discussions cover a variety of
imaging sensors ranging from state-of-the-art visible and infrared imaging
sensors, to RGB-D and mobile phone image sensors. A range of different
biometric modalities are also examined, including face, periocular and iris.

Topics and
features:

Presents a detailed introduction to the spectral
imaging of human skin, and describes the data collection of multispectral and
hyperspectral face images
Covers a range of face-based identification
technologies addressing challenges in the processing of face images in visible
and infrared spectral bands
Provides an overview of spoofing attacks and counter-measures
for FR systems, and analyzes the effects of digital image alterations on FR
algorithms
Investigates the processing of degraded face
photographs from ID documents, and examines mobile FR in still images and video
sequences
Proposes a state-of-the-art RGB-D FR algorithm, and suggests
algorithms for 3D-based FR as well as techniques blending 2D and 3D data
Discusses score normalization methods, and explores
the use of patterns in the sclera in order to improve the robustness of iris
recognition systems

This timely volume is a mine of useful information for
researchers, practitioners and students involved in image processing, computer
vision, biometrics and security.

Dr. Thirimachos Bourlai is an Assistant
Professor in the Lane Department of Computer Science and Electrical Engineering
at West Virginia University, Morgantown, WV, USA.