Invariant Description and Retrieval of Planar Shapes Using Radon Composite Features
Invariant Description and Retrieval of Planar Shapes Using Radon Composite Features
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DOI：
10.1109/tsp.2008.926692
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发表时间：
2008-10
影响因子：
5.4
通讯作者：
Yunwen Chen;Y. Q. Chen
中科院分区：
文献类型：
--
作者：
Yunwen Chen;Y. Q. Chen
提出了一种新的基于特征的平面形状不变描述子Radon复合特征。该方法不是直接在空间域分析形状，而是利用统计分析和频谱分析从Radon变换平面提取一些形状特征。该方法克服了现有形状表示方法的不足，无需任何归一化过程即可实现对常见几何变换的不变性，而归一化过程往往会导致不准确。一种新的基于RCFs的分层检索策略能够实现低复杂度和从粗到精的检索，在检索形状时能够准确执行，同时保持对变化的健壮性。实验表明，与几种最先进的方法相比，RCF提供了更高的识别度。
This paper proposes a novel feature-based invariant descriptor termed Radon composite features (RCFs) for planar shapes. Instead of analyzing shapes directly in the spatial domain, some shape features are extracted from the Radon transform plane using statistical and spectral analysis. The proposed method overcomes the drawbacks of existing shape representation techniques since it accomplishes the invariances to common geometrical transformations without any normalization process, which usually causes inaccuracies. A novel hierarchical strategy with RCFs can achieve low complexity and coarse-to-fine retrieval, and perform accurately when retrieving shapes, while remaining robust against variations. Experiments demonstrate that RCF provides a higher degree of discrimination as compared with several state-of-the-art approaches.