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Angular bisector network, a simplified generalized Voronoi diagram: application to processing complex intersections in biomedical images

机译:角平分线网,简化的广义Voronoi图:在生物医学图像中处理复杂相交的应用

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摘要

One of the major goals of computer vision is the research and the development of flexible methods for shape description. A large group of shape description techniques is given by heuristic approaches, which yield acceptable results in the description of simple shapes and regions. In this case, objects are represented by a planar graph with nodes symbolizing subregions from region decomposition, and region shape is then described by the graph properties. In the paper, the angular bisector network (ABN), a descriptor of polygonal shape, is used to automatically detect intersections between neurites of cell structures. Some properties of the ABN, such as linear algebraic complexity, easy extraction of characteristic points, etc., are very useful and experimental results are promising.
机译:计算机视觉的主要目标之一是研究和开发灵活的形状描述方法。启发式方法提供了大量形状描述技术,这些方法在简单形状和区域的描述中产生可接受的结果。在这种情况下,对象由平面图表示,节点表示区域分解中的子区域,然后由图形属性描述区域形状。在本文中,角平分线网络(ABN)是多边形的描述符,用于自动检测细胞结构的神经突之间的交点。 ABN的某些属性(例如线性代数复杂度,特征点的容易提取等)非常有用,并且实验结果很有希望。

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