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A Novel Measurement and Statistics of Similarity Cue for Edges in Contour Grouping

机译:轮廓分组中边缘相似提示的一种新的度量和统计

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Similarity is one of the important Gestalt laws for contour grouping. Edges are the basic elements of contour grouping. We define a novel measurement of edge similarity on the case of that an edge representation includes an estimate of the image intensity on either side of each edge. We discuss how to choose a proper feature to encode edge regions and which shape and size region is proper to edge similarity measurement. We also propose a new statistic of similarity cue which considers similarity on the basis of proximity, and which enhances the power of similarity cue in contour grouping effectively.
机译:相似度是轮廓分组的重要格式塔定律之一。边缘是轮廓分组的基本元素。我们定义了一种新的边缘相似性度量,即边缘表示包括每个边缘任一侧的图像强度估计。我们讨论如何选择合适的特征来编码边缘区域,以及哪种形状和大小区域适合边缘相似性测量。我们还提出了一种新的相似度提示统计量,该统计量基于接近度考虑相似度,并有效地增强了相似度提示在轮廓分组中的功能。

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