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Synopsis
Graph theory has strong historical roots in mathematics, especially in topology. Its birth is usually associated with the "four-color problem" posed by Francis Guthrie 1 in 1852, but its real origin probably goes back to the Seven Bridges of Konigsber ] g 2 problem proved by Leonhard Euler in 1736. A computational solution to these two completely different problems could be found after each problem was abstracted to the level of a graph model while ignoring such irrelevant details as country shapes or cross-river distances. In general, a graph is a nonempty set of points (vertices) and the most basic information preserved by any graph structure refers to adjacency relationships (edges) between some pairs of points. In the simplest graphs, edges do not have to hold any attributes, except their endpoints, but in more sophisticated graph structures, edges can be associated with a direction or assigned a label. Graph vertices can be labeled as well. A graph can be represented graphically as a drawing (vertex=dot, edge=arc), but, aslongaseverypairofadjacentpointsstaysconnected by the same edge, the graph vertices can be moved around on a drawing without changing the underlying graph structure. The expressive power of the graph models placing a special emphasis on c- nectivity between objects has made them the models of choice in chemistry, physics, biology, and other ?elds.
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Présentation de l'éditeur
This book presents novel graph-theoretic methods for complex computer vision and pattern recognition tasks. It presents the application of graph theory to low-level processing of digital images, presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, and provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks.
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Applied Graph Theory in Computer Vision and Pattern Recognition
Edité par
Springer, Berlin, Springer Berlin Heidelberg, Springer, 2007
ISBN 10 : 3540680195
ISBN 13 : 9783540680192
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Graph theory has strong historical roots in mathematics, especially in topology. Its birth is usually associated with the 'four-color problem' posed by Francis Guthrie 1 in 1852, but its real origin probably goes back to the Seven Bridges of Konigsber g 2 problem proved by Leonhard Euler in 1736. A computational solution to these two completely different problems could be found after each problem was abstracted to the level of a graph model while ignoring such irrelevant details as country shapes or cross-river distances. In general, a graph is a nonempty set of points (vertices) and the most basic information preserved by any graph structure refers to adjacency relationships (edges) between some pairs of points. In the simplest graphs, edges do not have to hold any attributes, except their endpoints, but in more sophisticated graph structures, edges can be associated with a direction or assigned a label. Graph vertices can be labeled as well. A graph can be represented graphically as a drawing (vertex=dot,edge=arc),but,aslongaseverypairofadjacentpointsst aysconnected by the same edge, the graph vertices can be moved around on a drawing without changing the underlying graph structure. The expressive power of the graph models placing a special emphasis on c- nectivity between objects has made them the models of choice in chemistry, physics, biology, and other elds. 266 pp. Englisch. N° de réf. du vendeur 9783540680192
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Applied Graph Theory in Computer Vision and Pattern Recognition
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Applied Graph Theory in Computer Vision and Pattern Recognition (Studies in Computational Intelligence, 52)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Applied Graph Theory in Computer Vision and Pattern Recognition
Edité par
Springer, Berlin, Springer Berlin Heidelberg, Springer, 2007
ISBN 10 : 3540680195
ISBN 13 : 9783540680192
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Graph theory has strong historical roots in mathematics, especially in topology. Its birth is usually associated with the 'four-color problem' posed by Francis Guthrie 1 in 1852, but its real origin probably goes back to the Seven Bridges of Konigsber g 2 problem proved by Leonhard Euler in 1736. A computational solution to these two completely different problems could be found after each problem was abstracted to the level of a graph model while ignoring such irrelevant details as country shapes or cross-river distances. In general, a graph is a nonempty set of points (vertices) and the most basic information preserved by any graph structure refers to adjacency relationships (edges) between some pairs of points. In the simplest graphs, edges do not have to hold any attributes, except their endpoints, but in more sophisticated graph structures, edges can be associated with a direction or assigned a label. Graph vertices can be labeled as well. A graph can be represented graphically as a drawing (vertex=dot,edge=arc),but,aslongaseverypairofadjacentpointsstaysconnected by the same edge, the graph vertices can be moved around on a drawing without changing the underlying graph structure. The expressive power of the graph models placing a special emphasis on c- nectivity between objects has made them the models of choice in chemistry, physics, biology, and other elds. N° de réf. du vendeur 9783540680192
Quantité disponible : 2 disponible(s)
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Applied Graph Theory in Computer Vision and Pattern Recognition
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Springer Berlin Heidelberg, 2007
ISBN 10 : 3540680195
ISBN 13 : 9783540680192
Neuf
Couverture rigide
Vendeur : moluna, Greven, Allemagne
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Gebunden. Etat : New. Will serve as a foundation for a variety of useful applications of the graph theory to computer vision, pattern recognition, and related areasCovers a representative set of novel graph-theoretic methods for complex computer vision and pattern reco. N° de réf. du vendeur 4898524
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Applied Graph Theory in Computer Vision and Pattern Recognition (Studies in Computational Intelligence, 52)
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Applied Graph Theory in Computer Vision and Pattern Recognition
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Applied Graph Theory in Computer Vision and Pattern Recognition
Edité par
Springer, 2007
ISBN 10 : 3540680195
ISBN 13 : 9783540680192
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Couverture rigide
Edition originale
Vendeur : Scarthin Books ABA, ILAB., Cromford, Royaume-Uni
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Book Hardcover. Etat : As New. No Jacket. 1st Edition. Springer, 2007. 1st Edition . As New/No Jacket. Book still in original shrink-wrap. N° de réf. du vendeur JP14350
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Applied Graph Theory in Computer Vision and Pattern Recognition
Edité par
Springer, 2007
ISBN 10 : 3540680195
ISBN 13 : 9783540680192
Ancien ou d'occasion
Couverture rigide
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 5072371
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Applied Graph Theory in Computer Vision and Pattern Recognition
Vendeur : Books Puddle, New York, NY, Etats-Unis
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Etat : New. pp. 276. N° de réf. du vendeur 26478842
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