Graph theory for image analysis: an approach based on the shortest spanning tree
Graph theory for image analysis: an approach based on the shortest spanning tree
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DOI：
10.1049/ip-f-1:19860025
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发表时间：
1986-04
期刊：
影响因子：
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通讯作者：
O. J. Morris;M.de J. Lee;A. Constantinides
中科院分区：
文献类型：
--
作者：
O. J. Morris;M.de J. Lee;A. Constantinides
本文描述了基于图论图像表示的图像分割和边缘检测方法。将图像映射到一个加权图上，并使用该图的生成树来描述图像中的区域或边缘。边缘检测是分割的双重问题。开发了许多方法，每种方法都提供了不同的分割或边缘检测技术。其中最简单的方法使用了最短生成树（SST），这个概念构成了其他改进方法的基础。这些进一步的方法利用全局图像信息，消除了简单形式的海表温度分割和其他像素链接算法的许多问题。所有提出的方法的一个重要特点是，区域可以用分层的方式来描述。
The paper describes methods of image segmentation and edge detection based on graph-theoretic representations of images. The image is mapped onto a weighted graph and a spanning tree of this graph is used to describe regions or edges in the image. Edge detection is shown to be a dual problem to segmentation. A number of methods are developed, each providing a different segmentation or edge detection technique. The simplest of these uses the shortest spanning tree (SST), a notion that forms the basis of the other improved methods. These further methods make use of global pictorial information, removing many of the problems of the SST segmentation in its simple form and of other pixel linking algorithms. An important feature in all of the proposed methods is that regions may be described in a hierarchical way.