Comparison and Combination of Ear and Face Images in Appearance-Based Biometrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Force field feature extraction for ear biometrics
Computer Vision and Image Understanding
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Unified 3D face and ear recognition using wavelets on geometry images
Pattern Recognition
Force field feature extraction for ear biometrics
Computer Vision and Image Understanding
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IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special issue on recent advances in biometrics
A study on the available biometric technologies used in order to control security in physical access
WSEAS Transactions on Systems and Control
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International Journal of Biometrics
Ear recognition by using neural networks
MMACTEE'09 Proceedings of the 11th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering
Recent advances in ear biometrics
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
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IWBRS'05 Proceedings of the 2005 international conference on Advances in Biometric Person Authentication
ACM Computing Surveys (CSUR)
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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 wass 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.