On ear biometrics

Today the most successful biometric based identification technologies such as fingerprint, iris, retina, palm and face recognition are used worldwide in both criminal investigations and high security facilities. These technologies are well-studied, but research shows they have many drawbacks which d...

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Bibliographic Details
Published inIEEE EUROCON 2009 pp. 327 - 332
Main Authors Kocaman, B., Kirci, M., Gunes, E.O., Cakir, Y., Ozbudak, O.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2009
Subjects
Aging
Biometrics
DCVA
Ear
Ear biometrics
Face recognition
Fingerprint recognition
FLDA
Iris
Lighting
LPP
PCA
Principal component analysis
Retina
Security
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Summary:Today the most successful biometric based identification technologies such as fingerprint, iris, retina, palm and face recognition are used worldwide in both criminal investigations and high security facilities. These technologies are well-studied, but research shows they have many drawbacks which decrease the success of the methods applied. Ear images are not affected by emotional expression, illumination, aging, poses and alike. In this study principal component analysis (PCA), fisher linear discriminant analysis (FLDA), discriminative common vector analysis (DCVA), and locality preserving projections (LPP) were applied to ear images for personal identification. The error and hit rates of four algorithms were calculated by random subsampling and k-fold cross validation.
ISBN:1424438608
9781424438600
DOI:10.1109/EURCON.2009.5167651