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Proceedings Paper

Texture discrimination using the Wigner-Ville distribution
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Paper Abstract

We present an effective method for texture segmentation and analysis using a local spectral method. The method combines the advantages of a high spectral resolution of a joint representation given by the Pseudo-Wigner distribution with an effective adaptive principal component analysis. Performance of the method is evaluated using fabric samples with defects, medical images, and crack detection in metallic surfaces. The examples demonstrate the discrimination power of the present method for detecting even very subtle changes in the homogeneity of textures.

Paper Details

Date Published: 19 November 2003
PDF: 8 pages
Proc. SPIE 5203, Applications of Digital Image Processing XXVI, (19 November 2003); doi: 10.1117/12.506881
Show Author Affiliations
Javier Hormigo, Univ. de Malaga (Spain)
Gabriel Cristobal, Instituto de Optica, CSIC (Spain)
Leon Cohen, CUNY/Hunter College (United States)
Lorenzo Galleani, Politecnico di Torino (Italy)
Bruce Suter, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 5203:
Applications of Digital Image Processing XXVI
Andrew G. Tescher, Editor(s)

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