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Sixth International Conference on Computational Intelligence and Multimedia Applications (ICCIMA'05)
Texture Classification Using Ridgelet Transform
Las Vegas, Nevada
August 16-August 18
ISBN: 0-7695-2358-7
S. Arivazhagan, Mepco Schlenk Enggineering College
L. Ganesan, A.C. College of Enggineering and Technology
T. G. Subash Kumar, Mepco Schlenk Enggineering College
Texture classification has long been an important research topic in image processing. Now a days classification based on wavelet transform is being very popular. Wavelets are very effective in representing objects with isolated point singularities, but failed to represent line singularities. Recently, ridgelet transform which deal effectively with line singularities in 2-D is introduced. It allows representing edges and other singularities along lines in a more efficient way. In this paper, the issue of texture classification based on ridgelet transform has been analyzed. Features are derived from the sub-bands of the ridgelet decomposition and are used for classification for a data set containing 20 texture images. Experimental results show that this approach allows obtaining high degree of success rate in classification.
Index Terms:
Ridgelet Transform, Radon transform, Texture classification, co-occurrence features
Citation:
S. Arivazhagan, L. Ganesan, T. G. Subash Kumar, "Texture Classification Using Ridgelet Transform," iccima, pp.321-326, Sixth International Conference on Computational Intelligence and Multimedia Applications (ICCIMA'05), 2005
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