DocumentCode :
2861097
Title :
Ear Biometrics Using 2D and 3D Images
Author :
Ping Yan ; Bowyer, K.W.
Author_Institution :
University of Notre Dame
fYear :
2005
fDate :
25-25 June 2005
Firstpage :
121
Lastpage :
121
Abstract :
We present results of the largest experimental investigation of ear biometrics to date. Approaches considered include a PCA ("eigen-ear") approach with 2D intensity images, achieving 63.8% rank-one recognition; a PCA approach with range images, achieving 55.3% Hausdorff matching of edge images from range images, achieving 67.5%, and ICP matching of the 3D data, achieving 84.1%. ICP based matching not only achieves the best performance, but also shows good scalability with size of dataset. The data set used represents over 300 persons, each with images acquired on at least two different dates.
Keywords :
Biometrics; Computer science; Ear; Feature extraction; Humans; Image recognition; Iterative closest point algorithm; Principal component analysis; Scalability; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition - Workshops, 2005. CVPR Workshops. IEEE Computer Society Conference on
Conference_Location :
San Diego, CA, USA
ISSN :
1063-6919
Print_ISBN :
0-7695-2372-2
Type :
conf
DOI :
10.1109/CVPR.2005.447
Filename :
1565433
Link To Document :
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