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Fuzzy objects and their boundaries

机译:模糊对象及其边界

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Abstract: Measured data are inherently inaccurate. Operations done on data for defining, visualizing, manipulating and analyzing object information should attempt to retain these inaccuracies as accurately as possible. The theory of fuzzy sets is a proper mathematical vehicle for this purpose. In this attempt, topological notions such as adjacency, connectedness, and boundary need to be developed starting from fuzzy sets. We develop such a framework in this paper and present algorithms for finding fuzzy connected components and boundaries in digital imagery. We demonstrate the usefulness of these algorithms in medical applications, particularly in separating objects that come close together which are otherwise difficult to segment using hard (non-fuzzy) criteria. !11
机译:摘要:测量数据本质上是不准确的。对用于定义,可视化,操纵和分析对象信息的数据进行的操作应尝试尽可能准确地保留这些不准确性。模糊集理论是实现此目的的合适数学工具。在这种尝试中,需要从模糊集开始发展诸如邻接,连通性和边界之类的拓扑概念。我们在本文中开发了这样的框架,并提出了用于在数字图像中查找模糊连接的分量和边界的算法。我们证明了这些算法在医学应用中的有用性,特别是在分离彼此靠近的对象时,否则很难使用硬(非模糊)标准进行分割。 !11

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