New methods for computing a shape¿s orientation and several shape measures for elongation, linearity, circularity, ellipticity, hyperbolicity, and parabolicity of 2D point sets are outlined. These measures are invariant to rotation, scaling, and translation. They are calculated very quickly as well. Among other things, we discover that the definition of elongation highly correlates with the definition of linearity. All of the shape measures are tested on digital curves and compared with existing methods. All of the methods work in real time. The goal was to find a way of identifying basic shapes in images. The motivation was to be able to use these basic shape descriptors as features in a computer vision system, where more complicated shapes can be seen as collections of basic ones. This way, a computer should one day be able to identify the objects in even the most complicated scenes we deal with in our daily lives.
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New methods for computing a shape¿s orientation and several shape measures for elongation, linearity, circularity, ellipticity, hyperbolicity, and parabolicity of 2D point sets are outlined. These measures are invariant to rotation, scaling, and translation. They are calculated very quickly as well. Among other things, we discover that the definition of elongation highly correlates with the definition of linearity. All of the shape measures are tested on digital curves and compared with existing methods. All of the methods work in real time. The goal was to find a way of identifying basic shapes in images. The motivation was to be able to use these basic shape descriptors as features in a computer vision system, where more complicated shapes can be seen as collections of basic ones. This way, a computer should one day be able to identify the objects in even the most complicated scenes we deal with in our daily lives.
The author completed his PhD at the University of Ottawa in the fall of 2008, in the field of Computer Science. His research interests lie in Computer Vision, Image Processing, and Pattern Recognition. His Masters was done at Carleton University, in 2005. Applications of his work are found in surveillance and security, and medical imaging.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - New methods for computing a shape s orientation andseveral shape measures for elongation, linearity,circularity, ellipticity, hyperbolicity, andparabolicity of 2D point sets are outlined. Thesemeasures are invariant to rotation, scaling, andtranslation. They are calculated very quickly aswell. Among other things, we discover that thedefinition of elongation highly correlates with thedefinition of linearity. All of the shape measuresare tested on digital curves and compared withexisting methods. All of the methods work in realtime. The goal was to find a way of identifying basicshapes in images. The motivation was to be able touse these basic shape descriptors as features in acomputer vision system, where more complicated shapescan be seen as collections of basic ones. This way, acomputer should one day be able to identify theobjects in even the most complicated scenes we dealwith in our daily lives. N° de réf. du vendeur 9783639179552
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Taschenbuch. Etat : Neu. Measuring conic properties and shape orientations | 2D point sets | Milo Stojmenovi | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639179552 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 101531628
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. 140 pages. 8.66x5.91x0.32 inches. In Stock. N° de réf. du vendeur 3639179552
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