Paper Info
Title
Three Dimensional Palmprint Recognition Using Linear Discriminant Analysis Method
Abstract
As a significant biometric technique, 3D palm print authentication is better than 2D palm print authentication in several aspects. Previous work on 3D palm print recognition has concentrated on two aspects: (1) extracting the texture and line features using the binary image of 3D palm print, (2) extracting the orientation features using the Gabor filter and competitive code. In this paper we extract, for the first time, the 3D palm print features using the appearance-based linear discriminant analysis (LDA) method. The appearance-based LDA method can extract the global algebraic features of the biometrics. These features have been proven to have strong discriminability. We also investigated the relationship between the recognition accuracy and the resolution of the 3D palm print image. The experimental results show that the 3D palm print images with resolution and are better for 3D palm print recognition. The experiment results also show the feasibility of our method.
Year
DOI
Venue
2011
10.1109/IBICA.2011.31
IBICA
Keywords
Field
DocType
gabor filter,palm print,appearance-based lda method,palm print recognition,recognition accuracy,palm print authentication,palm print image,binary image,appearance-based linear discriminant analysis,competitive code,dimensional palmprint recognition,linear discriminant analysis method,image resolution,image recognition,image texture,data mining,three dimensional,message authentication,accuracy,feature extraction,statistical analysis
Computer vision,Palm print,Pattern recognition,Computer science,Image texture,Binary image,Feature extraction,Gabor filter,Artificial intelligence,Linear discriminant analysis,Biometrics,Image resolution
Conference
Citations 
PageRank 
References 
3
0.43
12
Authors
2
Name
Order
Citations
PageRank
Jinrong Cui1544.67
Yong Xu299.53