Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/46496
Title: Texture classification through multiscale orientation histogram analysis
Authors: Alemán-Flores, Miguel 
Álvarez-Leon, Luis 
UNESCO Clasification: 220990 Tratamiento digital. Imágenes
120601 Construcción de algoritmos
120602 Ecuaciones diferenciales
120326 Simulación
Keywords: Multi scale analysis
New approaches
Orientation histograms
Reliable methods
Scale Factor, et al
Issue Date: 2003
Journal: Lecture Notes in Computer Science 
Conference: 4th International Conference on Scale Space Methods in Computer Vision 
Abstract: This work presents a new approach to texture classification, in which orientation histograms and multiscale analysis have been combined to achieve a reliable method. From the outputs of a set of filters, the orientation and magnitude of the gradient in every point of a texture are estimated. By combining the orientations and relative magnitudes of the gradient, we build an orientation histogram for each texture. We have used Fourier analysis to measure the similarity between the histograms of different textures, considering the effects of a change in the size or orientation of the image to make our method invariant under these phenomena. Since different textures may generate very similar histograms, we have analyzed the evolution of these histograms at different scales, extracting a scale factor for each couple of compared textures to adjust the filters which are applied to them when the multiscale analysis is carried out.
URI: http://hdl.handle.net/10553/46496
ISBN: 978-3-540-40368-5
ISSN: 0302-9743
DOI: 10.1007/3-540-44935-3_33
Source: Griffin L.D., Lillholm M. (eds) Scale Space Methods in Computer Vision. Scale-Space 2003. Lecture Notes in Computer Science, vol 2695. Springer, Berlin, Heidelberg
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