This paper addresses the problem of segmenting an image into regions. We define a
predicate for measuring the evidence for a boundary between two regions using a graph …

Minimum cut/maximum flow algorithms on graphs have emerged as an increasingly useful
tool for exactor approximate energy minimization in low-level vision. The combinatorial …

This paper explores a statistical basis for a process often described in computer vision:
image segmentation by region merging following a particular order in the choice of regions …

In this paper, we introduce simple graph clustering methods based on minimum cuts within
the graph. The clustering methods are general enough to apply to any kind of graph but are …

In a clustering problem one has to partition a set of elements into homogeneous and well-
separated subsets. From a graph theoretic point of view, a cluster graph is a vertex-disjoint …

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Feature space clustering is a popular approach to image segmentation, in which a feature
vector of local properties (such as intensity, texture or motion) is computed at each pixel. The …

Many machine learning algorithms for clustering or dimensionality reduction take as input a
cloud of points in Euclidean space, and construct a graph with the input data points as …

The region's internal properties (color, texture,...) help to identify them and their external
relations (adjacency, inclusion,...) are used to build groups of regions having a particular …

Any reasonably large group of individuals, families, states, and parties exhibits the
phenomenon of subgroup formations within the group such that the members of each group …