Title: Handbook of Iris Recognition
            
                Advances in Computer Vision and Pattern Recognition
Description: More than 100 trillion iris comparisons are now being performed on a daily basis, a number that is rapidly growing. This is breath-taking progress for a field that is arguably just twenty years old.The first book of its kind devoted entirely to the subject, the Handbook of Iris Recognition introduces the reader to this exciting, rapidly developing, technology of today and tomorrow. Blending insights from the editors’ own work, and exploiting their broad overview of the field, this authoritative collection introduces the reader to the state of the art in iris recognition technology.Topics and features:With a Foreword by the “father of iris recognition,” Professor John Daugman of Cambridge UniversityPresents work from an international selection of preeminent researchers, reflecting the uses of iris recognition in many different social contextsProvides viewpoints from researchers in government, industry and academia, highlighting how iris recognition is both a thriving industry and an active research areaSurveys previous developments in the field, and covers topics ranging from the low-level (e.g., physics of iris image acquisition) to the high level (e.g., alternative non-Daugman approaches to iris matching)Introduces many active and open areas of research in iris recognition, including cross-wavelength matching and iris template agingThis comprehensive text/reference is an essential resource for anyone wishing to improve their understanding of iris recognition technology, be they practitioners in industry, managers and executives, or researchers searching for new insights and ideas.Dr. Mark J. Burge is Senior Principal Scientist at the MITRE Corporation, McLean, VA, USA. Dr. Kevin W. Bowyer is the Schubmehl-Prein Family Professor and Department Chair of Computer Science and Engineering at the University of Notre Dame, IN, USA.
Subjects: Biometric identification, Pattern recognition systems, Optical pattern recognition, Biometrie, Regenbogenhaut, Maschinelles Sehen, Personenkontrolle, Erkennung, Mustererkennung, Pattern perception, Computer science