NDLI: Rotation invariant feature extraction using Ridgelet and Fourier transforms

Content Provider	Springer Nature Link
Author	Chen, G. Y. Bui, T. D. Krzyżak, A.
Copyright Year	2006
Abstract	In this paper, we present a novel descriptor for feature extraction by using a combination of Ridgelets and Fourier transform. We have successfully implemented ridgelets on the circular disk containing the pattern and applied Fourier transform on the resulting ridgelet coefficients to extract rotation-invariant features for pattern recognition. The descriptor is very robust to Gaussian noise even when the noise level is high. Experimental results show that the new descriptor is a very good choice for pattern recognition.
Starting Page	83
Ending Page	93
Page Count	11
File Format	PDF
ISSN	14337541
Journal	Pattern Analysis & Applications
Volume Number	9
Issue Number	1
e-ISSN	1433755X
Language	English
Publisher	Springer Verlag
Publisher Date	2006-05-11
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Feature extraction Image descriptors Character recognition Pattern recognition Ridgelets Fourier transform
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition

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Rotation invariant feature extraction using Ridgelet and Fourier transforms