A survey on ear biometrics

Recognizing people by their ear has recently received significant attention in the literature. Several reasons account for this trend: first, ear recognition does not suffer from some problems associated with other non-contact biometrics, such as face recognition; second, it is the most promising ca...

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Bibliographic Details
Published in:	ACM computing surveys 2013-02, Vol.45 (2), p.1-35
Main Authors:	Abaza, Ayman, Ross, Arun, Hebert, Christina, Harrison, Mary Ann, Nixon, Mark
Format:	Article
Language:	eng
Subjects:	Applied sciences Artificial intelligence Biometrics Classification Computer science control theory systems Computer systems and distributed systems. User interface Data processing. List processing. Character string processing Ear ear recognition/detection earprints Ears & hearing Exact sciences and technology Face recognition Facial recognition technology Illumination Indoor Memory organisation. Data processing Pattern recognition Pattern recognition. Digital image processing. Computational geometry person verification/identification Recognition Software Studies Surveillance
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Summary:	Recognizing people by their ear has recently received significant attention in the literature. Several reasons account for this trend: first, ear recognition does not suffer from some problems associated with other non-contact biometrics, such as face recognition; second, it is the most promising candidate for combination with the face in the context of multi-pose face recognition; and third, the ear can be used for human recognition in surveillance videos where the face may be occluded completely or in part. Further, the ear appears to degrade little with age. Even though current ear detection and recognition systems have reached a certain level of maturity, their success is limited to controlled indoor conditions. In addition to variation in illumination, other open research problems include hair occlusion, earprint forensics, ear symmetry, ear classification, and ear individuality. This article provides a detailed survey of research conducted in ear detection and recognition. It provides an up-to-date review of the existing literature revealing the current state-of-art for not only those who are working in this area but also for those who might exploit this new approach. Furthermore, it offers insights into some unsolved ear recognition problems as well as ear databases available for researchers.
ISSN:	0360-0300 1557-7341