基于标记分组的曲线结构跨尺度标注

E. Saund
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引用次数: 32

摘要

提出了一种线条图和边缘图像中多尺度曲线结构的标注算法。驻留在空间索引和比例索引数据结构中的符号曲线元素标记表示适合图像数据的圆弧。令牌是通过一个从小到大的分组过程来计算的,使用贪婪的最佳优先策略来选择对新令牌的支持。所得到的图像描述是丰富和冗余的,因为图像轮廓的给定片段可以由不同尺度的多个标记来描述,并且在任何给定尺度上可以由多个标记来描述。此属性有助于基于曲线元素属性的图像部分的选择和表征。
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Labeling of curvilinear structure across scales by token grouping
An algorithm for labeling curvilinear structure at multiple scales in line drawings and edge images is presented. Symbolic curve-element tokens residing in a spatially indexed and scale-indexed data structure denote circular arcs fit to image data. Tokens are computed via a small-to-large scale grouping procedure using a greedy best-first strategy for choosing the support of new tokens. The resulting image description is rich and redundant in that a given segment of image contour may be described by multiple tokens at different scales, and by more than one token at any given scale. This property facilitates selection and characterization of portions of the image based on curve-element attributes.<>
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