A fuzzy connectedness - based road automatic extraction method from SPOT image is presented.
提出了一种基于模糊连接度的SPOT图像公路信息全自动提取算法。
First, the object with interest is extracted and a new image scene is constructed using fuzzy connectedness-based method.
首先计算整幅图像的模糊连接度，通过阈值分割提取出感兴趣的对象，并将模糊连接度作为图像的冗余特征；
The new method of road semi-automatic extraction was proposed, which was based on multiseeded-fuzzy connectedness combined with road feature in SPOT image.
结合模糊连接度理论和SPOT影像上道路的表现特性提出了主干道路半自动提取的方法。
Secondly the method combines with the road characteristic and USES fuzzy connectedness to join the break road segment, and at last farther process to form the whole road network.
接着结合道路局部特征运用模糊连接度连接断裂路段，最后根据道路走向进一步完善整个道路轮廓。
The fuzzy membership is defined by not only the relation between a sample and its cluster center, but also those among samples, which is described by the fuzzy connectedness among samples.
在确定样本的隶属度时，不仅考虑了样本与类中心之间的关系，还考虑了类中各个样本之间的关系，并采用模糊连接度来度量类中各个样本之间的关系。
In this paper, three measure of the connectedness of a fuzzy graph: fuzzy connectivity, fuzzy edge connectivity, fuzzy nuclearity and their properties are presented.
本文给出了衡量模糊图连通性的三个度量：模糊连通度、模糊边连通度与模糊核度及其相关的性质。
In this paper, three measure of the connectedness of a fuzzy graph: fuzzy connectivity, fuzzy edge connectivity, fuzzy nuclearity and their properties are presented.
本文给出了衡量模糊图连通性的三个度量：模糊连通度、模糊边连通度与模糊核度及其相关的性质。
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