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A novel shape descriptor based on von Mises distributions

机译:基于冯·米塞斯分布的新型形状描述符

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Since most local descriptors of shape are not scale invariant, we usually make the line drawings or object contours in an image database the same size through scale normalization, before applying shape recognition procedures. Drawings produced by scale normalization are suitable for such descriptors if the whole of the original drawings are similar in shape. They are, however, not suitable if parts of each drawing are drawn using a different scale. In this paper, we propose a novel scale invariant descriptor that does not require scale normalization. The experimental results on shape matching and retrieval show the effectiveness of our descriptor, compared to several conventional descriptors.
机译:由于大多数形状的局部描述符不是尺度不变的,因此通常在应用形状识别程序之前,通过尺度归一化,使图像数据库中的线图或对象轮廓具有相同的大小。如果整个原始图的形状相似,则通过比例尺归一化生成的图适用于此类描述符。但是,如果每个图形的各个部分使用不同的比例绘制,则它们不适用。在本文中,我们提出了一种不需要尺度归一化的新颖尺度不变描述符。与几种常规描述符相比,形状匹配和检索的实验结果表明了我们的描述符的有效性。

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