Relational matching is a method for finding the best
correspondences betweenstructural descriptions. It is
widely used in computer vision for the recognition and
location of objects in digital images. For this purpose, the
digital images and the object models are represented by
structural descriptions. The matching algorithm then has to
determine which image elements and object model parts
correspond.
This book is the result of abasic study of relational
matching. The book focuses particularly on the evaluation of
correspondences. In order to find the best match, one needs
a measure to evaluate the quality of a match. The author
reviews the evaluation measures that have been suggested
over the past few decades and presents a new measure based
on information theory. The resulting theorycombines
matching strategies, information theory, and tree search
methods. For the benefit of the reader, comprehensive
introductions are given to all these topics.