Iris recognition using 2D-LDA + 2D-PCA

Author

Chen, Wen-Shiung ; Chuan, Chi-An ; Shih, Sheng-Wen ; Chang, Shun-Hsun

Author_Institution

Dept. of Electr. Eng., Nat. Chi Nan Univ., Chi Nan

fYear

2009

fDate

19-24 April 2009

Firstpage

869

Lastpage

872

Abstract

This paper presents a biometric iris recognition using 2D-LDA with embedding 2D-PCA. A new approach that the 2D-PCA is embedded into the 2D-LDA to improve its performance is proposed. The approach first finds the most concentrated training samples in each class, and uses the sample mean to represent the class. Then the 2D-PCA is adopted to find the projection matrix which can scatter the variance between classes. The results show that the new approach has an encouraging performance. The recognition rate up to 99.20% can be achieved.

Keywords

biometrics (access control); image recognition; principal component analysis; 2D-LDA; 2D-PCA; biometric iris recognition; concentrated training samples; projection matrix; Biometrics; Feature extraction; Gabor filters; Image resolution; Image texture analysis; Iris recognition; Linear discriminant analysis; Principal component analysis; Scattering; Vectors; Biometric Recognition; Iris; Linear Discriminant Analysis (LDA); Principal Component Analysis (PCA);

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on

Conference_Location

Taipei

ISSN

1520-6149

Print_ISBN

978-1-4244-2353-8

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2009.4959722

Filename

4959722