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.

Bibliographic Information

Book Title: Relational Matching
Editors: G. Vosselman
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/3-540-55798-9
Publisher: Springer Berlin, Heidelberg
eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag Berlin Heidelberg 1992
Softcover ISBN: 978-3-540-55798-2Published: 10 September 1992
eBook ISBN: 978-3-540-47287-2Published: 03 July 2005
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: X, 18
Topics: Theory of Computation, Artificial Intelligence, Pattern Recognition, Models and Principles, Software Engineering/Programming and Operating Systems

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Relational Matching

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