Abstract
We introduce a technique for measuring local scale, based on a special property of the so-called total variational (TV) flow. For TV flow, pixels change their value with a speed that is inversely proportional to the size of the region they belong to. Exploiting this property directly leads to a region based measure for scale that is well-suited for texture discrimination. Together with the image intensity and texture features computed from the second moment matrix, which measures the orientation of a texture, a sparse feature space of dimension 5 is obtained that covers the most important descriptors of a texture: magnitude, orientation, and scale. A demonstration of the performance of these features is given in the scope of texture segmentation.
Our research is partly funded by the project WE 2602/1-1 of the Deutsche Forschungsgemeinschaft (DFG). This is gratefully acknowledged. We also want to thank Mikaël Rousson and Rachid Deriche for many interesting discussions on texture segmentation.
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Brox, T., Weickert, J. (2004). A TV Flow Based Local Scale Measure for Texture Discrimination. In: Pajdla, T., Matas, J. (eds) Computer Vision - ECCV 2004. ECCV 2004. Lecture Notes in Computer Science, vol 3022. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24671-8_46
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DOI: https://doi.org/10.1007/978-3-540-24671-8_46
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