Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/27505
Title: A Fourier-LDA approach for image recognition
Authors: Jing, XY
Tang, YY
Zhang, D 
Keywords: Fourier transform
Fourier-LDA approach (FLA)
Frequency-band selection
Linear discrimination analysis (LDA)
Two-dimensional separability judgment
Issue Date: 2005
Publisher: Elsevier
Source: Pattern recognition, 2005, v. 38, no. 3, p. 453-457 How to cite?
Journal: Pattern recognition 
Abstract: Fourier transform and linear discrimination analysis (LDA) are two commonly used techniques of image processing and recognition. Based on them, we propose a Fourier-LDA approach (FLA) for image recognition. It selects appropriate Fourier frequency bands with favorable linear separability by using a two-dimensional separability judgment. Then it extracts two-dimensional linear discriminative features to perform the classification. Our experimental results on different image data prove that FLA obtains better classification performance than other linear discrimination methods.
URI: http://hdl.handle.net/10397/27505
ISSN: 0031-3203
EISSN: 1873-5142
DOI: 10.1016/j.patcog.2003.09.020
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