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A Robust Shape Retrieval Method Based on Hough-Radii

机译:基于Hough-Radii的鲁棒形状检索方法

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A novel shape similarity retrieval algorithm (Hough-Radii) for 2-D objects is presented. The method uses a polar transformation of the contour points to get the shape descriptor that is invariant to translation, rotation and scaling. We take the maximum point in the generalized Hough transform (GHT) mapping array as the reference point for polar transform that is different from the traditional Centroid-Radii method where the geometric centre was taken as the origin. The effectiveness of our algorithm is illustrated in the retrieval of two databases of 99 and 216 shapes provided by Sebastian et al. The experimental results show the competitiveness of our approach to some others especially in the retrieval of partially occluded and missing images.
机译:提出了一种用于2-D对象的新颖形状相似性检索算法(Hough-RADII)。该方法使用轮廓点的极性变换,以获取不变的形状描述符,以便转换,旋转和缩放。我们将广义Hough变换(GHT)映射阵列中的最大点作为极性变换的参考点,其与传统的质心-RADII方法不同,几何中心被视为原点。我们的算法的有效性在Sebastian等人提供的99和216个形状的两个数据库中检索。实验结果表明,我们对某些其他人的竞争力特别是在检索部分封闭和缺失的图像中。

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