Graphs are a powerful and versatile tool useful in various subfields of science and
engineering. In many applications, for example, in pattern recognition and computer vision, it …

In this paper we explore how to embed symbolic relational graphs with unweighted edges in
a pattern-space. We adopt a graph-spectral approach. We use the leading eigenvectors of …

We consider the use of medial surfaces to represent symmetries of 3-D objects. This allows
for a qualitative abstraction based on a directed acyclic graph of components and also a …

We propose a new algorithm for error-correcting subgraph isomorphism detection from a set
of model graphs to an unknown input graph. The algorithm is based on a compact …

This paper describes a Bayesian framework for performing relational graph matching by
discrete relaxation. Our basic aim is to draw on this framework to provide a comparative …

One important task of site monitoring is change detection from aerial images. Change, in
general, can be of various types. In this paper we address the problem of developmental …

In retrieval from image databases, evaluation of similarity, based both on the appearance of
spatial entities and on their mutual relationships, depends on content representation based …

Graph structures have proven computationally cumbersome for pattern analysis. The reason
for this is that, before graphs can be converted to pattern vectors, correspondences must be …

Perceptual organization offers an elegant framework to group low-level features that are
likely to come from a single object. We offer a novel strategy to adapt this grouping process …

This paper describes a novel framework for comparing and matching corrupted relational
graphs. The paper develops the idea of edit-distance originally introduced for graph …