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The Resource Relational matching, G. Vosselman

Relational matching, G. Vosselman

Creator
Summary
"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."--PUBLISHER'S WEBSITE
Language
eng
Work
Publication
Extent
ix, 190 pages
Isbn
9783540557982
Instance
Label
Relational matching
Title
Relational matching
Statement of responsibility
G. Vosselman
Creator
Subject
Language
eng
Summary
"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."--PUBLISHER'S WEBSITE
Member of
Cataloging source
DLC
http://library.link/vocab/creatorDate
1963-
http://library.link/vocab/creatorName
Vosselman, G.
Dissertation note
Thesis (doctoral)--Rheinische Friedrich-Wilhelms-Universität, Bonn.
Illustrations
illustrations
Index
no index present
LC call number
TA1632
LC item number
.V6715 1992
Literary form
non fiction
Nature of contents
bibliography
http://library.link/vocab/subjectName
  • Image processing
  • Computer vision
  • Matching theory
  • reconnaissance objet
  • recherche heuristique
  • localisation
  • arbre recherche
  • théorie information
  • appariement
  • Traitement d'images
  • Vision par ordinateur
  • Computer vision
  • Image processing
  • Matching theory
  • Vision par ordinateur
  • Relationales Matching
Label
Relational matching, G. Vosselman
Instantiates
Publication
Bibliography note
Includes bibliographical references
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Dimensions
25 cm.
Extent
ix, 190 pages
Isbn
9783540557982
Lccn
92025541
Media category
unmediated
Media MARC source
rdamedia
Media type code
  • n
Other physical details
illustrations
System control number
  • (OCoLC)26211419
  • (OCoLC)ocm26211419
Label
Relational matching, G. Vosselman
Publication
Bibliography note
Includes bibliographical references
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Dimensions
25 cm.
Extent
ix, 190 pages
Isbn
9783540557982
Lccn
92025541
Media category
unmediated
Media MARC source
rdamedia
Media type code
  • n
Other physical details
illustrations
System control number
  • (OCoLC)26211419
  • (OCoLC)ocm26211419

Subject

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