Clustering of singular value decomposition of image data with applications to texture classification
Alireza Tavakoli Targhi, Azad Shademan · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
In this paper, some applications of a local version of Singular Value Decomposition (SVD) to texture classification and texture segmentation are studied. We introduce two measures, obtained from SVD transform, which capture some of the perceptual and conceptual features in an image. One of the measures classifies the textures by their roughness and structures. Experimental results show that these measures are suitable for texture clustering and image segmentation and they are robust relative to changes in lighting.