Biometrics deal with recognition of individuals based on their physiological or behavioural characteristics. Researchers have done extensive studies on biometrics such as fingerprint, face, palm print, iris and gait. Ear, a viable new class of biometrics, has certain advantages over face and fingerprint, which are the two most common biometrics in both academic research and industrial applications.

This book explores all aspects of 3D ear recognition: representation, detection, recognition, indexing and performance prediction. It uses large datasets to quantify and compare the performance of various techniques.

Features and topics include: Ear detection and recognition in 2D image - 3D object recognition and 3D biometrics - 3D ear recognition - Performance comparison and prediction.

The techniques discussed will be of great interest to researchers, developers and decision makers who are involved in robust human recognition by computer for a large number of practical applications.

From the reviews:

"‘Human ear [recognition] is a new class of relatively stable biometrics,’ that has drawn the attention of not only researchers, but also forensics experts, criminologists, and security experts … . the book will be of great interest to researchers … . I recommend reading the book as a stepping stone to further research work on human ear recognition, from the viewpoints of both researchers and forensics experts." (J. Myerson, ACM Computing Reviews, December, 2008)