At the frontier of research, this book offers complete coverage of human ear recognition. It 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.
Biometrics deals with recognition of individuals based on their physiological or behavioral characteristics. The human ear is a new feature in biometrics that has several merits over the more common face, fingerprint and iris biometrics. Unlike the fingerprint and iris, it can be easily captured from a distance without a fully cooperative subject, although sometimes it may be hidden with hair, scarf and jewellery. Also, unlike a face, the ear is a relatively stable structure that does not change much with the age and facial expressions.
Human Ear Recognition by Computer is the first book on the automatic recognition of human ears. It presents an entire range of computational algorithms for recognition of humans by their ears. These algorithms have been tested and validated on the largest databases that are available today. Specific algorithms addressed include:
Ear helix/anti-helix based representation
Global-to-local registration
Ear recognition using helix/anti-helix representation
Ear recognition using a new local surface patch representation