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Proceedings Paper

Texture Classification Using Multi-resolution Rotation--Invariant Operators
Author(s): Nanda K. Alapati; Arthur C. Sanderson
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Paper Abstract

A set of 2-D multi-resolution, rotation-invariant operators is developed. These operators are based on 1-D projection functions which form a basis set for local image patterns. The operators are complex with the magnitude rotation-invariant and the phase carrying directional information. Convolution of an operator with an image yields a complex output image containing magnitude and phase information. Application of a set of such operators at different resolutions to an image yields a set of features which may then be used for classification and phase analysis. The operators are evaluated with respect to their ability to perform texture analysis. Texture classification of four structurally similar textures is performed with better than 90% accuracy of interior regions. Also demonstrated is the ability of the operators to provide orientation information about textures.

Paper Details

Date Published: 11 December 1985
PDF: 12 pages
Proc. SPIE 0579, Intelligent Robots and Computer Vision IV, (11 December 1985); doi: 10.1117/12.950780
Show Author Affiliations
Nanda K. Alapati, Carnegie-Mellon University (United States)
Arthur C. Sanderson, Carnegie-Mellon University (United States)


Published in SPIE Proceedings Vol. 0579:
Intelligent Robots and Computer Vision IV
David P. Casasent, Editor(s)

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