Combining wavelet transform and Orthogonal Centroid Algorithm for ear recognition

Author

Hai-Long, Zhao ; Zhi-Chun, Mu

Author_Institution

Sch. of Inf. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China

fYear

2009

fDate

8-11 Aug. 2009

Firstpage

228

Lastpage

231

Abstract

In recent years, automatic ear recognition has become a popular research. Effective feature extraction is one of the most important steps in Content-based ear image retrieval applications. In this paper, a new approach is proposed that the low frequency sub-images are obtained by utilizing two-dimensional wavelet transform and then the features are extracted by applying Orthogonal Centroid Algorithm to the low frequency sub-images. The experimental results on USTB ear database prove that the proposed method can overcome the Small Sample Size problem and get better performance of recognition speed than conventional PCA+LDA algorithm.

Keywords

ear; feature extraction; image recognition; image retrieval; wavelet transforms; automatic ear recognition; content-based ear image retrieval; feature extraction; orthogonal centroid algorithm; wavelet transform; Continuous wavelet transforms; Discrete wavelet transforms; Ear; Eigenvalues and eigenfunctions; Feature extraction; Frequency; Image databases; Image reconstruction; Scattering; Wavelet transforms; LDA; PCA; ear recognition; orthogonal centroid; wavelet transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-4519-6

Electronic_ISBN

978-1-4244-4520-2

Type

conf

DOI

10.1109/ICCSIT.2009.5234392

Filename

5234392