Palmprint recognition using Fisher's linear discriminant

Xiang Qian Wu; Kuan Quan Wang; Dapeng Zhang

Palmprint recognition using Fisher's linear discriminant

Xiang Qian Wu
, Kuan Quan Wang
, Dapeng Zhang

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

21 Citations (Scopus)

Abstract

In this paper, a novel method for palmprint recognition is proposed. In this method, each pixel of a palmprint image is considered as a coordinate in a high-dimensional image space. A linear projection based on Fisher's linear discriminant (FLD) is used to project palmprints from this high-dimensional space to a significantly lower dimensional feature space, in which the ratio of the determinant of the between-class scatter to that of the within-class scatter is maximized. High accuracies of 99% and 99.2% have been obtained in one-to-one matching and one-to-300 matching test respectively and the speed of this method is rapid enough for real-time palmprint recognition.

Original language	English
Title of host publication	International Conference on Machine Learning and Cybernetics
Pages	3150-3154
Number of pages	5
Volume	5
Publication status	Published - 1 Dec 2003
Event	2003 International Conference on Machine Learning and Cybernetics - Xi'an, China Duration: 2 Nov 2003 → 5 Nov 2003

Conference

Conference	2003 International Conference on Machine Learning and Cybernetics
Country/Territory	China
City	Xi'an
Period	2/11/03 → 5/11/03

Keywords

Biometrics
Fisher's linear discriminant
Linear projection
Palmprint recognition

ASJC Scopus subject areas

Artificial Intelligence

Cite this

@inproceedings{f8058182438b420d8e4c6fa8906f80fb,

title = "Palmprint recognition using Fisher's linear discriminant",

abstract = "In this paper, a novel method for palmprint recognition is proposed. In this method, each pixel of a palmprint image is considered as a coordinate in a high-dimensional image space. A linear projection based on Fisher's linear discriminant (FLD) is used to project palmprints from this high-dimensional space to a significantly lower dimensional feature space, in which the ratio of the determinant of the between-class scatter to that of the within-class scatter is maximized. High accuracies of 99\% and 99.2\% have been obtained in one-to-one matching and one-to-300 matching test respectively and the speed of this method is rapid enough for real-time palmprint recognition.",

keywords = "Biometrics, Fisher's linear discriminant, Linear projection, Palmprint recognition",

author = "Wu, \{Xiang Qian\} and Wang, \{Kuan Quan\} and Dapeng Zhang",

year = "2003",

month = dec,

day = "1",

language = "English",

isbn = "0780378652",

volume = "5",

pages = "3150--3154",

booktitle = "International Conference on Machine Learning and Cybernetics",

note = "2003 International Conference on Machine Learning and Cybernetics ; Conference date: 02-11-2003 Through 05-11-2003",

}

TY - GEN

T1 - Palmprint recognition using Fisher's linear discriminant

AU - Wu, Xiang Qian

AU - Wang, Kuan Quan

AU - Zhang, Dapeng

PY - 2003/12/1

Y1 - 2003/12/1

N2 - In this paper, a novel method for palmprint recognition is proposed. In this method, each pixel of a palmprint image is considered as a coordinate in a high-dimensional image space. A linear projection based on Fisher's linear discriminant (FLD) is used to project palmprints from this high-dimensional space to a significantly lower dimensional feature space, in which the ratio of the determinant of the between-class scatter to that of the within-class scatter is maximized. High accuracies of 99% and 99.2% have been obtained in one-to-one matching and one-to-300 matching test respectively and the speed of this method is rapid enough for real-time palmprint recognition.

AB - In this paper, a novel method for palmprint recognition is proposed. In this method, each pixel of a palmprint image is considered as a coordinate in a high-dimensional image space. A linear projection based on Fisher's linear discriminant (FLD) is used to project palmprints from this high-dimensional space to a significantly lower dimensional feature space, in which the ratio of the determinant of the between-class scatter to that of the within-class scatter is maximized. High accuracies of 99% and 99.2% have been obtained in one-to-one matching and one-to-300 matching test respectively and the speed of this method is rapid enough for real-time palmprint recognition.

KW - Biometrics

KW - Fisher's linear discriminant

KW - Linear projection

KW - Palmprint recognition

UR - https://www.scopus.com/pages/publications/1542366724

M3 - Conference article published in proceeding or book

SN - 0780378652

VL - 5

SP - 3150

EP - 3154

BT - International Conference on Machine Learning and Cybernetics

T2 - 2003 International Conference on Machine Learning and Cybernetics

Y2 - 2 November 2003 through 5 November 2003

ER -

Palmprint recognition using Fisher's linear discriminant

Abstract

Conference

Keywords

ASJC Scopus subject areas

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