Title :
Invariant Ridgelet-Fourier Descriptor for Pattern Recognition
Author :
Chen, G.Y. ; Bui, T.D. ; Krzyzak, A.
Author_Institution :
Dept. of Comput. Sci., Concordia Univ., Montreal, Que.
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
Keywords :
Fourier transforms; Gaussian noise; feature extraction; Fourier transform; Gaussian noise; circular disk; invariant ridgelet-Fourier descriptor; pattern recognition; ridgelet coefficients; ridgelet transform; rotation-invariant feature extraction; Computer science; Feature extraction; Fourier transforms; Gaussian noise; Image analysis; Noise level; Noise robustness; Pattern analysis; Pattern recognition; Wavelet transforms;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.722
