Abstract
We show how the perceptual grouping method known as tensor voting can be applied to grey-level images by introducing the use of local orientation tensors computed from a set of Gabor filters. While inputs formerly consisted of binary images or sparse edgel maps, our extension yields oriented input tokens and the locations of junctions as input to the perceptual grouping. In order to handle dense input maps, the tensor voting framework is extended by the introduction of grouping fields with inhibitory regions. Results of the method are demonstrated on example images.
We gratefully acknowledge partial funding of this work by the Deutsche Forschungsgemeinschaft under grant Me1289/7-1 “KomForm”.
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Massad, A., Babós, M., Mertsching, B. (2002). Application of the Tensor Voting Technique for Perceptual Grouping to Grey-Level Images. In: Van Gool, L. (eds) Pattern Recognition. DAGM 2002. Lecture Notes in Computer Science, vol 2449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45783-6_37
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DOI: https://doi.org/10.1007/3-540-45783-6_37
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