三角化图像对象的测地线。基于直角三角剖分和曲率三角剖分的图像逼近
Geodesics of Triangulated Image Object Shapes. Approximating Image Shapes via Rectilinear and Curvilinear Triangulations
摘要：
本文介绍了影像目标三角剖分的测地线。被认为是直线和曲线三角形的形状。图像对象形状的三角剖分导致被称为神经复合体的集合，其为形状几何学的研究提供了可行的基础。神经复合体是具有公共顶点的填充三角形的集合。每个神经复合体三角形都有一个称为辐条的延伸部分，它提供了覆盖形状内部的有效手段。这导致了一个基于测地线的度量形状近似，提供了一个简单的方法来评估，比较和分类的图像对象的形状与高灵敏度。
英文摘要：
This paper introduces the geodesics of triangulated image object shapes. Both rectilinear and curvilinear triangulations of shapes are considered. The triangulation of image object shapes leads to collections of what are known as nerve complexes that provide a workable basis for the study of shape geometry.A nerve complex is a collection of filled triangles with a common vertex. Each nerve complex triangle has an extension called a spoke, which provides an effective means of covering shape interiors. This leads to a geodesic-based metric for shape approximation which offers a straightforward means of assessing, comparing and classifying the shapes of image objects with high acuity.
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