Rapid and brief communications: A Fourier-LDA approach for image recognition

Authors:
Xiao-Yuan Jing;Yuan-Yan Tang;David Zhang
Affiliations:
Bio-Computing Research Centre and Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, Guangdong Province, China;Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong;Department of Computing, Hong Kong Polytechnic University, Kowloon, Hong Kong
Venue:
Pattern Recognition
Year:
2005

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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.