NDLI: Texture classification using ridgelet transform

Content Provider	IEEE Xplore Digital Library
Author	Arivazhagan, S. Ganesan, L. Subash Kumar, T.G.
Copyright Year	2005
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Mepco Schlenk Eng. Coll., India (Arivazhagan, S.)
Abstract	Texture classification has long been an important research topic in image processing. Classification based on the wavelet transform has become very popular. Wavelets are very effective in representing objects with isolated point singularities, but failed to represent line singularities. Recently, a ridgelet transform which deals 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 a ridgelet transform has been analyzed. Features are derived from 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 to obtain a high degree of success in classification.
Starting Page	321
Ending Page	326
File Size	109084
Page Count	6
File Format	PDF
ISBN	0769523587
DOI	10.1109/ICCIMA.2005.55
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-08-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image texture analysis Wavelet transforms Wavelet packets Educational institutions Image analysis Filter bank Gabor filters Head Biomedical signal processing Autocorrelation co-occurrence features Ridgelet Transform Radon transform Texture classification
Content Type	Text
Resource Type	Article

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