کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
530297 | 869756 | 2012 | 19 صفحه PDF | دانلود رایگان |

The beneficial properties of the Radon transform make it a 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 patterns 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.
► We generalize the R-transform/R-signature for pattern description/recognition.
► The generalization maintains beneficial properties of the conventional one.
► The domain of this generalization is discussed.
► The discrimination power and sensitivity to noise are investigated.
► The generic R-signature has superior performance to comparison methods.
Journal: Pattern Recognition - Volume 45, Issue 6, June 2012, Pages 2145–2163