Archivio Istituzionale della RicercaWe 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 discriminative power of the present method for detecting even very subtle changes in the homogeneity of textures.
Texture discrimination using the Wigner-Ville distribution / Hormigo, J.; Cristobal, G.; Cohen, L.; Galleani, Lorenzo; Suter, B.. - STAMPA. - 5203:(2003), pp. 155-162. (Intervento presentato al convegno SPIE’s 48th Annual Meeting tenutosi a San Diego, USA nel 3-8 August, 2003) [10.1117/12.506881].
Texture discrimination using the Wigner-Ville distribution
GALLEANI, Lorenzo;
2003
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 discriminative power of the present method for detecting even very subtle changes in the homogeneity of textures.
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https://hdl.handle.net/11583/1663160
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