A rotation invariant feature extraction for 3D ear recognition

Author

Yiliang Li ; Zhichun Mu ; Hui Zeng

Author_Institution

Sch. of Autom. & Electr. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China

fYear

2013

fDate

25-27 May 2013

Firstpage

3671

Lastpage

3675

Abstract

In this paper, we use a new method, which based on the spherical harmonics transform, to extract 3D ear rotation invariant feature from 3D ear data. And a 3D ear recognition system was built through matching ear spherical harmonics feature, which is rotation invariant in mathematical theory. Utilizing its rotation invariant property, the 3D ear recognition method could be strongly robust in pose variation. A Rank-1 recognition rate, achieved in experiment, is 96.4% on a data set of 415 subjects, and processing time also has been reduced, comparing to the well-known ICP algorithm.

Keywords

ear; feature extraction; image matching; mathematical analysis; 3D ear data; 3D ear recognition; 3D ear rotation invariant feature extraction; ear spherical harmonics feature matching; mathematical theory; pose variation; rotation invariant property; spherical harmonics transform; Ear; Feature extraction; Harmonic analysis; Image recognition; Iterative closest point algorithm; Pattern recognition; Transforms; 3D ear recognition; Rotation invariant ear feature; Spherical harmonics transform; Spherical sampling;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2013 25th Chinese

Conference_Location

Guiyang

Print_ISBN

978-1-4673-5533-9

Type

conf

DOI

10.1109/CCDC.2013.6561586

Filename

6561586