Paper Info
Title
An efficient ear recognition technique invariant to illumination and pose
Abstract
This paper presents an efficient ear recognition technique which derives benefits from the local features of the ear and attempt to handle the problems due to pose, poor contrast, change in illumination and lack of registration. It uses (1) three image enhancement techniques in parallel to neutralize the effect of poor contrast, noise and illumination, (2) a local feature extraction technique (SURF) on enhanced images to minimize the effect of pose variations and poor image registration. SURF feature extraction is carried out on enhanced images to obtain three sets of local features, one for each enhanced image. Three nearest neighbor classifiers are trained on these three sets of features. Matching scores generated by all three classifiers are fused for final decision. The technique has been evaluated on two public databases, namely IIT Kanpur ear database and University of Notre Dame ear database (Collections E). Experimental results confirm that the use of proposed fusion significantly improves the recognition accuracy.
Year
DOI
Venue
2013
10.1007/s11235-011-9621-2
Telecommunication Systems
Keywords
Field
DocType
Biometrics,Ear recognition,Image enhancement,Fusion
k-nearest neighbors algorithm,Ear recognition,Computer vision,Pattern recognition,Computer science,Feature extraction,Artificial intelligence,Invariant (mathematics),Biometrics,Image registration
Journal
Volume
Issue
ISSN
52
3
1018-4864
Citations 
PageRank 
References 
21
0.74
16
Authors
2
Name
Order
Citations
PageRank
Surya Prakash115919.79
Phalguni Gupta280582.58