Two-Directional PCA/LDA

Two-Directional PCA/LDA

David Zhang (Hong Kong Polytechnic University, Hong Kong), Xiao-Yuan Jing (ShenZhen Graduate School of Harbin Institute of Technology, China) and Jian Yang (Hong Kong Polytechnic University, Hong Kong)
DOI: 10.4018/978-1-59140-830-7.ch012
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Abstract

This chapter introduces a two-directional PCA/LDA approach that is a useful statistical technique applied to biometric authentication. We first describe both bi-directional PCA (BDPCA) and BDPCA plus LDA. Then, some basic models and definitions related to two-directional PCA/LDA approach are given. Next, we discuss two-directional PCA plus LDA. And, finally, the experimental results and chapter summary are given.

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Table of Contents
Acknowledgments
David Zhang, Xiao-Yuan Jing, Jian Yang
Chapter 1
David Zhang, Xiao-Yuan Jing, Jian Yang
In this chapter, we briefly introduce biometrics image discrimination (BID) technologies. First, we define and describe types of biometrics and... Sample PDF
An Introduction to Biometrics Image Discrimination (BID)
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Chapter 2
David Zhang, Xiao-Yuan Jing, Jian Yang
In this chapter, we first describe some basic concepts of PCA, a useful statistical technique that can be used in many fields, such as face patterns... Sample PDF
Principle Component Analysis
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Chapter 3
David Zhang, Xiao-Yuan Jing, Jian Yang
This chapter deals with issues related to linear discriminant analysis (LDA). In the introduction, we indicate some basic conceptions of LDA. Then... Sample PDF
Linear Discriminant Analysis
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Chapter 4
David Zhang, Xiao-Yuan Jing, Jian Yang
In this chapter, we show some PCA/LDA applications in biometrics. Based on the introductions to both PCA and LDA mentioned in Chapters II and III... Sample PDF
PCA/LDA Applications in Biometrics
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Chapter 5
David Zhang, Xiao-Yuan Jing, Jian Yang
This chapter shows a special LDA approach called optimal discrimination vectors (ODV), which requires that every discrimination vector satisfy the... Sample PDF
Statistical Uncorrelation Analysis
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Chapter 6
David Zhang, Xiao-Yuan Jing, Jian Yang
This chapter shows the solutions of LDA for small sample-size (SSS) problems. We first give an overview on the existing LDA regularization... Sample PDF
Solutions of LDA for Small Sample Size Problems
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Chapter 7
An Improved LDA Approach  (pages 187-204)
David Zhang, Xiao-Yuan Jing, Jian Yang
This chapter gives an improved LDA (ILDA) approach. After a short review and comparison of major linear discrimination methods, including the... Sample PDF
An Improved LDA Approach
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Chapter 8
David Zhang, Xiao-Yuan Jing, Jian Yang
This chapter provides a feature extraction approach that combines the discrete cosine transform (DCT) with LDA. The DCT-based frequency-domain... Sample PDF
Discriminant DCT Feature Extraction
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Chapter 9
David Zhang, Xiao-Yuan Jing, Jian Yang
In this chapter, we discuss some other typical BID improvements, including dual eigenspaces method (DEM) and post-processing on LDA-based method for... Sample PDF
Other Typical BID Improvements
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Chapter 10
David Zhang, Xiao-Yuan Jing, Jian Yang
This chapter introduces a complete kernel Fisher discriminant analysis (KFD) that is a useful statistical technique applied to biometric... Sample PDF
Complete Kernal Fisher Discrimination Analysis
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Chapter 11
David Zhang, Xiao-Yuan Jing, Jian Yang
This chapter presents two straightforward image projection techniques — two-dimensional (2D) image matrix-based principal component analysis (IMPCA... Sample PDF
2D Image Matrix-Based Discriminator
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Chapter 12
Two-Directional PCA/LDA  (pages 287-328)
David Zhang, Xiao-Yuan Jing, Jian Yang
This chapter introduces a two-directional PCA/LDA approach that is a useful statistical technique applied to biometric authentication. We first... Sample PDF
Two-Directional PCA/LDA
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Chapter 13
David Zhang, Xiao-Yuan Jing, Jian Yang
This chapter describes feature fusion techniques using complex discriminator. After the introduction, we first introduce serial and parallel feature... Sample PDF
Feature Fusion Using Complex Descriminator
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