Non-iterative two-dimensional linear discriminant analysis

Kohei Inoue; Kiichi Urahama

doi:10.1109/ICPR.2006.860

Non-iterative two-dimensional linear discriminant analysis

Kohei Inoue, Kiichi Urahama

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

18 Citations (Scopus)

Abstract

Linear discriminant analysis (LDA) is a well-known scheme for feature extraction and dimensionality reduction of labeled data in a vector space. Recently, LDA has been extended to two-dimensional LDA (2DLDA), which is an iterative algorithm for data in matrix representation. In this paper, we propose non-iterative algorithms for 2DLDA. Experimental results show that the non-iterative algorithms achieve competitive recognition rates with the iterative 2DLDA, while they are computationally more efficient than the iterative 2DLDA.

Original language	English
Title of host publication	Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006
Pages	540-543
Number of pages	4
Volume	2
DOIs	https://doi.org/10.1109/ICPR.2006.860
Publication status	Published - 2006
Event	18th International Conference on Pattern Recognition, ICPR 2006 - Hong Kong, China Duration: Aug 20 2006 → Aug 24 2006

Other

Other	18th International Conference on Pattern Recognition, ICPR 2006
Country/Territory	China
City	Hong Kong
Period	8/20/06 → 8/24/06

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering
Computer Vision and Pattern Recognition
Hardware and Architecture

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10.1109/ICPR.2006.860

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title = "Non-iterative two-dimensional linear discriminant analysis",

abstract = "Linear discriminant analysis (LDA) is a well-known scheme for feature extraction and dimensionality reduction of labeled data in a vector space. Recently, LDA has been extended to two-dimensional LDA (2DLDA), which is an iterative algorithm for data in matrix representation. In this paper, we propose non-iterative algorithms for 2DLDA. Experimental results show that the non-iterative algorithms achieve competitive recognition rates with the iterative 2DLDA, while they are computationally more efficient than the iterative 2DLDA.",

author = "Kohei Inoue and Kiichi Urahama",

year = "2006",

doi = "10.1109/ICPR.2006.860",

language = "English",

isbn = "0769525210",

volume = "2",

pages = "540--543",

booktitle = "Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006",

note = "18th International Conference on Pattern Recognition, ICPR 2006 ; Conference date: 20-08-2006 Through 24-08-2006",

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T1 - Non-iterative two-dimensional linear discriminant analysis

AU - Inoue, Kohei

AU - Urahama, Kiichi

PY - 2006

Y1 - 2006

N2 - Linear discriminant analysis (LDA) is a well-known scheme for feature extraction and dimensionality reduction of labeled data in a vector space. Recently, LDA has been extended to two-dimensional LDA (2DLDA), which is an iterative algorithm for data in matrix representation. In this paper, we propose non-iterative algorithms for 2DLDA. Experimental results show that the non-iterative algorithms achieve competitive recognition rates with the iterative 2DLDA, while they are computationally more efficient than the iterative 2DLDA.

AB - Linear discriminant analysis (LDA) is a well-known scheme for feature extraction and dimensionality reduction of labeled data in a vector space. Recently, LDA has been extended to two-dimensional LDA (2DLDA), which is an iterative algorithm for data in matrix representation. In this paper, we propose non-iterative algorithms for 2DLDA. Experimental results show that the non-iterative algorithms achieve competitive recognition rates with the iterative 2DLDA, while they are computationally more efficient than the iterative 2DLDA.

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U2 - 10.1109/ICPR.2006.860

DO - 10.1109/ICPR.2006.860

M3 - Conference contribution

AN - SCOPUS:34047221157

SN - 0769525210

SN - 9780769525211

VL - 2

SP - 540

EP - 543

BT - Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006

T2 - 18th International Conference on Pattern Recognition, ICPR 2006

Y2 - 20 August 2006 through 24 August 2006

ER -

Non-iterative two-dimensional linear discriminant analysis

Abstract

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