Title :
An evaluation of face and ear biometrics
Author :
Victor, Barnabas ; Bowyer, Kevin ; Sarka, Sudeep
Author_Institution :
Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA
Abstract :
Face recognition based on principal component analysis is a heavily researched topic in computer vision. The ear has been proposed as a biometric, with claimed advantages over the face. We have applied the PCA approach to images of the face and ear using the same set of subjects. Testing was done with three different gallery/probe combinations. For faces we have: 1) probes of same day but different expression, 2) probes of a different day but similar expression, and 3) probes of different day and different expression. Analogously, for ears, we have: 1) probes of same day but other ear, 2) probes of a different day but same ear, and 3) probes of different day and other ear Results indicate that the face provides a more reliable biometric than the ear.
Keywords :
computer vision; eigenvalues and eigenfunctions; face recognition; principal component analysis; computer vision; ear biometrics; face biometrics; face recognition; principal component analysis; Biometrics; Computer vision; Ear; Face detection; Face recognition; Lighting; Pixel; Principal component analysis; Probes; Testing;
Conference_Titel :
Pattern Recognition, 2002. Proceedings. 16th International Conference on
Print_ISBN :
0-7695-1695-X
DOI :
10.1109/ICPR.2002.1044746