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Attribute-space connectivity and connected filters

机译:属性空间连接性和连接的过滤器

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In this paper connected operators from mathematical morphology are extended to a wider class of operators, which are based on connectivities in higher dimensional spaces, similar to scale spaces, which will be called attribute-spaces. Though some properties of connected filters are lost, granulometries can be defined under certain conditions, and pattern spectra in most cases. The advantage of this approach is that regions can be split into constituent parts before filtering more naturally than by using partitioning connectivities. Furthermore, the approach allows dealing with overlap, which is impossible in connectivity. A theoretical comparison to hyperconnectivity suggests the new concept is different. The theoretical results are illustrated by several examples. These show how attribute-space connected filters merge the ability of filtering based on local structure using classical, structuring-element-based filters to the object-attribute-based filtering of connected filters, and how this differs from similar attempts using second-generation connectivity.
机译:在本文中,从数学形态学出发的连通算子被扩展到更广泛的算子类别,这些算子基于高维空间(类似于尺度空间)中的连通性,被称为属性空间。尽管失去了连接的过滤器的某些属性,但可以在某些条件下定义粒度,并且在大多数情况下可以确定图案光谱。这种方法的优势在于,与使用分区连接相比,可以在更自然地进行过滤之前将区域分为多个组成部分。此外,该方法允许处理重叠,这在连接中是不可能的。与超连接性的理论比较表明,新概念是不同的。几个例子说明了理论结果。这些显示了属性空间连接的过滤器如何将使用经典的,基于结构元素的过滤器将基于局部结构的过滤功能合并到连接的过滤器的基于对象属性的过滤中,以及这与使用第二代连接的类似尝试有何不同。

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