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Shape matching and retrieval via contour multi-scale decomposition

机译:通过轮廓多尺度分解进行形状匹配和检索

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In this paper, we propose a new shape decomposition method based on visual perception for shape matching and retrieval which uses the protrusive corners under multiple scales. Our approach composes of a multi-scale shape decomposition procedure and a contour segments matching procedure. Firstly, morphological operations are used for more stable and visual perceptual corners to get the contour segmented under multiple scales. Secondly, a human perceptual custom and the sequence of segments are introduced and modeled in matching algorithm with segments described by SC descriptor. Finally, an ultimate similarity between two shapes is conducted by a fusion strategy based on multiple scales. Our method is evaluated on well-known shape databases including MPEG-7 and Kimia databases. The experimental retrieval results and the comparison with other methods clearly indicate the effectiveness of the proposed approach.
机译:在本文中,我们提出了一种基于视觉感知的形状分解和匹配的新方法,该方法使用多个尺度下的凸角。我们的方法由多尺度形状分解过程和轮廓线段匹配过程组成。首先,形态学运算用于更稳定和视觉感知的拐角,以在多个尺度下分割轮廓。其次,引入了人类的感知习惯和片段序列,并在匹配算法中对建模对象的片段进行了建模。最后,通过基于多个尺度的融合策略来实现两个形状之间的最终相似性。我们的方法在包括MPEG-7和Kimia数据库在内的知名形状数据库中进行了评估。实验检索结果以及与其他方法的比较清楚地表明了该方法的有效性。

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