DocumentCode :
1905486
Title :
Palmprint recognition using kernel PCA of Gabor features
Author :
Ekinci, Murat ; Aykut, Murat
Author_Institution :
Dept. of Comput. Eng., Karadeniz Tech. Univ., Trabzon
fYear :
2008
fDate :
27-29 Oct. 2008
Firstpage :
1
Lastpage :
6
Abstract :
This paper presents a new method for automatic palmprint recognition based on kernel PCA method by integrating the Gabor wavelet representation of palm images. Gabor wavelets are first applied to derive desirable palmprint features. The Gabor transformed palm images exhibit strong characteristics of spatial locality, scale, and orientation selectivity. These images can produce salient features that are most suitable for palmprint recognition. The kernel PCA method then nonlinearly maps the Gabor-wavelet image into a high-dimensional feature space. The proposed algorithm has been successfully tested on two different public data sets from the PolyU palmprint databases for which the samples were collected in two different sessions.
Keywords :
Gabor filters; feature extraction; image recognition; image representation; image sampling; principal component analysis; wavelet transforms; Gabor features; Gabor wavelet representation; PolyU palmprint databases; automatic palmprint recognition; kernel PCA; salient features; Biometrics; Computer vision; Face recognition; Image databases; Image recognition; Kernel; Lighting; Pattern recognition; Principal component analysis; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Information Sciences, 2008. ISCIS '08. 23rd International Symposium on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-2880-9
Electronic_ISBN :
978-1-4244-2881-6
Type :
conf
DOI :
10.1109/ISCIS.2008.4717873
Filename :
4717873
Link To Document :
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