Effects of image compression on ear biometrics

• Published in: IET biometrics Vol. 5; no. 3; pp. 252 - 261
• Main Authors: Rathgeb, Christian, Pflug, Anika, Wagner, Johannes, Busch, Christoph
• Format: Journal Article
• Language: English
• Published: Stevenage The Institution of Engineering and Technology 01.09.2016; John Wiley & Sons, Inc
• Subjects: Algorithms; Automation; Biometric recognition systems; Biometrics; biometrics (access control); Cameras; Compression; data compression; Ear; ear biometrics; ear detection algorithm; ear recognition algorithm; Forensic engineering; forensic scenarios; Forensic science; Forensic sciences; image coding; Image compression; Image transmission; Impact analysis; Investigations; Object recognition; outer ear; Pattern recognition; Quality standards; Recognition; Software; Surveillance; surveillance cameras; uncompressed ear database; visual databases; surveillance cameras; data compression; ear detection algorithm; uncompressed ear database; forensic scenarios; image compression; ear recognition algorithm; ear biometrics; visual databases; outer ear; biometrics (access control); image coding
• ISSN: 2047-4938; 2047-4946; 2047-4946
• DOI: 10.1049/iet-bmt.2015.0098

An ear recognition system represents a powerful tool in forensic applications. Even in case the facial characteristic of a suspect is partly or fully covered an image of the outer ear may suffice to reveal a subject's identity. In forensic scenarios imagery may stem from surveillance cameras of environments where image compression is common practice to overcome limitations of storage or transmission capacities. Yet, the impact of severe image compression on ear recognition has remained undocumented. In this work the authors analyse the influence of different state-of-the-art image compression standards on ear detection and ear recognition algorithms. Evaluations conducted on an uncompressed ear database are considered with respect to different stages in the processing chain of an ear recognition system where compression may be applied, representing the most relevant forensic scenarios. Experimental results are discussed in detail highlighting the potential and limitations of automated ear recognition in presence of image compression.