Texture Boundary Detection — A Structural Approach
Perception of different textures is caused by differences in distribution of properties of texture elements. However, in practice it is difficult to extract useful texture elements, especially from natural images in which texture elements exist at various scales. To extract texture elements of all sizes a multiscale approach is unavoidable. This paper describes a multiscale method, based on measurements in a Laplacian-of-Gaussian scale-space, to extract texture elements. Histograms are used to describe the distribution of properties of extracted texture elements in a region. The edge significance at a pixel reflects the difference in the histograms of the regions surrounding the pixel. High edge significance pixels constitute the texture boundaries. Performance of the approach is shown for various natural textured images.
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