Generic R-transform for invariant pattern representation

Thai V. Hoang, S. Tabbone
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引用次数: 2

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 with a generic view on a popular Radon-based pattern descriptor, the R-signature, bringing in a class of descriptors spatially describing patterns at all the directions and at different levels. The domain of this class and the selection of its representative are also discussed. Theoretical arguments validate the robustness of the generic R-signature to additive noise and experimental results show its effectiveness.
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用于不变模式表示的通用r变换
Radon变换的有利特性使其成为一种有用的中间表示,用于从模式图像中提取用于索引/匹配的不变特征。本文以一种流行的基于氡的模式描述符r -签名的一般观点重新审视了这个问题,引入了一类描述符在空间上描述所有方向和不同层次的模式。讨论了该类的研究领域及其代表人物的选择。理论论证验证了通用r特征对加性噪声的鲁棒性,实验结果表明了它的有效性。
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