Finger-Articular Back Texture Recognition Based on Log Gabor

Author

Shangling, Song ; Changyu, Wang ; Liangmo, Mei ; Zhi, Liu

Author_Institution

Dept. of Inf. Sci. & Eng., Shandong Univ., Jinan, China

Volume

6

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

221

Lastpage

226

Abstract

This paper presents a new biometrics pattern, finger-articular back texture recognition using Log Gabor wavelet. Firstly, hand back image was captured by special imaging device. Then joint texture was segmented, and located by a sliding window. The texture features were extracted based on the Log Gabor wavelet transform and were classified by the corresponding feature encoding classifier. The experiment results shown that finger-articular back texture can be used for personal authentication, Log Gabor wavelet is better than Gabor wavelet for pattern extraction, and the equal right rate was 98.21% in Finger-articular back texture recognition.

Keywords

biometrics (access control); feature extraction; image recognition; image texture; wavelet transforms; Log Gabor wavelet transform; biometrics pattern; feature encoding classifier; finger-articular back texture recognition; hand back image; joint texture; personal authentication; sliding window; texture features; Biometrics; Fingerprint recognition; Fingers; Geometry; Image edge detection; Image resolution; Image segmentation; Pattern recognition; Security; Veins; Finger-Articular Back Texture Recognition; Gabor; Log Gabor; biometric recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2009. ICNC '09. Fifth International Conference on

Conference_Location

Tianjin

Print_ISBN

978-0-7695-3736-8

Type

conf

DOI

10.1109/ICNC.2009.561

Filename

5367149