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Pattern Recognition Letters 33 (2012) 182–190

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Pattern Recognition Letters
journal homepage: www.elsevier.com/locate/patrec

Ear recognition based on local information fusion
Li Yuan ⇑, Zhi chun Mu
School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China

article

infoArticle history:
Received 3 August 2010
Available online 20 October 2011
Communicate by M.S. Nixon
Keywords:
Ear recognition
Partial occlusion
Neighborhood preserving embedding
Sub-classifier fusion

abstract
Ears have rich structural features that are almost invariant with increasing age and facial expression variations. Therefore ear recognition has become an effective and appealingapproach to non-contact biometric recognition. This paper gives an up-to date review of research works on ear recognition. Current 2D
ear recognition approaches achieve good performance in constrained environments. However the recognition performance degrades severely under pose, lighting and occlusion. This paper proposes a 2D ear
recognition approach based on local information fusion to dealwith ear recognition under partial occlusion. Firstly, the whole 2D image is separated to sub-windows. Then, Neighborhood Preserving Embedding is used for feature extraction on each sub-window, and we select the most discriminative subwindows according to the recognition rate. Each sub-window corresponds to a sub-classifier. Thirdly, a
sub-classifier fusion approach is used for recognition withpartially occluded images. Experimental
results on the USTB ear dataset and UND dataset have illustrated that using only few sub-windows we
can represent the most meaningful region of the ear, and the multi-classifier model gets higher recognition rate than using the whole image for recognition.
Ó 2011 Elsevier B.V. All rights reserved.

1. Introduction
As an emerging biometrics technology, earrecognition is
attracting more and more attention in biometrics recognition.
Human ears offer some distinct advantages over other biometric
modalities: they have a wealthy of structural features that are permanent with increasing age from about 8–70 years old, and they
are not affected by the expression variations (Burge and Burger,
2000). Ear image is smaller under the same resolution,which can
be favorable in some situations, such as the audio-visual person
authentication using speech and ear images for mobile phone
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usage. According to the evaluations in Choras (2006), the ear is a
kind of highly accepted biometrics, and subjects to be identified
feel more comfortable with ear images enrollment compared to
face images enrollment. Ear recognition is user-friendly and canbe used in non-intrusive recognition and surveillance scenarios.
Ears have played a significant role in forensic science for many
years (Nixon et al., 2010), especially in the United States, where an
ear classification system based on manual measurements has been
developed by Iannarelli, and has been in use for more than 40 years
(Iannarelli, 1989). The United States Immigration andNaturalization Service (INS) has a form giving specifications for the photograph that indicate that the right ear should be visible (INS Form
M-378 (6-92)). During crime scene investigation or airplane
crashes, earmarks are often used for identification (Alberink and
⇑ Corresponding author. Tel.: +86 10 62334995.
E-mail address: yuanli64@hotmail.com (L. Yuan).
0167-8655/$ - see front matter Ó 2011Elsevier B.V. All rights reserved.
doi:10.1016/j.patrec.2011.09.041

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Ruifrok, 2007; Choras, 2007). The history of using ear images or
ear prints shows their potential value for human identification
applications such as access control, security monitoring and video
surveillance (Hurley et al., 2008).
An ear recognition system usually involves ear detection, feature extraction and ear...