The generalization of the R-transform for invariant pattern representation

Thai V. Hoang 1, * Salvatore Tabbone 1
* Auteur correspondant
1 QGAR - Querying Graphics through Analysis and Recognition
LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : The beneficial properties of the Radon transform make it an useful intermediate representation for the extraction of invariant features from pattern images for the purpose of indexing/matching. This paper revisits the problem of Radon image utilization with a generic view on a popular Radon transform-based transform and pattern descriptor, the R-transform and R-signature, bringing in a class of transforms and descriptors spatially describing patterns at all directions and at different levels, while maintaining the beneficial properties of the conventional R-transform and R-signature. The domain of this class, which is delimited due to the existence of singularities and the effect of sampling/quantization and additive noise, is examined. Moreover, the ability of the generic R-transform to encode the dominant directions of pattern is also discussed, adding to the robustness to additive noise of the generic R-signature. The stability of dominant direction encoding by the generic R-transform and the superiority of the generic R-signature over existing invariant pattern descriptors on grayscale and binary noisy datasets have been confirmed by experiments.
Type de document :
Article dans une revue
Pattern Recognition, Elsevier, 2012, 〈10.1016/j.patcog.2011.11.007〉
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Soumis le : dimanche 13 novembre 2011 - 17:51:52
Dernière modification le : mardi 24 avril 2018 - 13:51:33
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Thai V. Hoang, Salvatore Tabbone. The generalization of the R-transform for invariant pattern representation. Pattern Recognition, Elsevier, 2012, 〈10.1016/j.patcog.2011.11.007〉. 〈inria-00637631〉



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