UID:
almahu_9948621643002882
Format:
X, 18 p.
,
online resource.
Edition:
1st ed. 1992.
ISBN:
9783540472872
Series Statement:
Lecture Notes in Computer Science, 628
Content:
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.
Note:
Computer vision and matching -- A classification of matching methods -- Formal description of relational matching -- Problem definition and contributions of the thesis -- Information theory:Selected Topics -- Evaluation of mappings between relational descriptions -- Tree search methods and heuristics -- Relational image and model description -- Evaluation functions for object location -- Strategy and performance of the tree search for object location -- Summary and discussion.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783662205174
Additional Edition:
Printed edition: ISBN 9783540557982
Language:
English
DOI:
10.1007/3-540-55798-9
URL:
https://doi.org/10.1007/3-540-55798-9
