A Versatile Framework for Handling Subdivided Geometric ObjectsCombinatorial Maps: Efficient Data Structures for Computer Graphics and Image Processing gathers important ideas related to combinatorial maps and explains how the maps are applied in geometric modeling and image processing. It focuses on two subclasses of combinatorial maps: n-Gmaps and n-maps.Suitable for researchers and graduate students in geometric modeling, computational and discrete geometry, computer graphics, and image processing and analysis, the book presents the data structures, operations, and algorithms that are useful in handling subdivided geometric objects. It shows how to study data structures for the explicit representation of subdivided geometric objects and describes operations for handling the structures. The book also illustrates results of the design of data structures and operations.

A Versatile Framework for Handling Subdivided Geometric ObjectsCombinatorial Maps: Efficient Data Structures for Computer Graphics and Image Processing gathers important ideas related to combinatorial maps and explains how the maps are applied in geometric modeling and image processing. It focuses on two subclasses of combinatorial maps: n-Gmaps an

A Versatile Framework for Handling Subdivided Geometric ObjectsCombinatorial Maps: Efficient Data Structures for Computer Graphics and Image Processing gathers important ideas related to combinatorial maps and explains how the maps are applied in geometric modeling and image processing. It focuses on two subclasses of combinatorial maps: n-Gmaps and n-maps.Suitable for researchers and graduate students in geometric modeling, computational and discrete geometry, computer graphics, and image processing and analysis, the book presents the data structures, operations, and algorithms that are useful in handling subdivided geometric objects. It shows how to study data structures for the explicit representation of subdivided geometric objects and describes operations for handling the structures. The book also illustrates results of the design of data structures and operations.

A Versatile Framework for Handling Subdivided Geometric ObjectsCombinatorial Maps: Efficient Data Structures for Computer Graphics and Image Processing gathers important ideas related to combinatorial maps and explains how the maps are applied in geometric modeling and image processing. It focuses on two subclasses of combinatorial maps: n-Gmaps an

In 2005, the twelfth edition of the conference Discrete Geometry for Computer Imagery was held in Poitiers, France, April 13-15, 2005. The conference was organized by the laboratory SIC ("Signal, Image, Communications") of the University of Poitiers, Centre National de la Recherche Scienti?que and the Technical Committee 18 of the International Association for Pattern Recog- tion. DGCI 2005 was sponsored by the Faculty of Science, the University of Poitiers, the Conseil G' en' eral de la Vienne and the Region of Poitou-Charentes. The aim of the conference was to present recent advances in both theoretical aspects and applications in discrete geometry. This year's conference was organized in combination with the 5th Workshop B on Graph- ased Representations in Pattern Recognition,April 11-13, 2005 also organizedinPoitiers.TheworkshopGbRaimsatusinggraph-basedstructuresin image analysis. There is a strong connection between the community interested in the GbR workshop and the discrete geometry community. For this reason, for the?rsttime,boththeworkshopandtheDGCIconferencewereorganizedin the same place, with a common session of four papers, two submitted to GbR and two to DGCI.The DGCI conference attracted again for this edition many excellent papers, with 53 submitted papers from 21 countries. After careful reviewing by two and sometimesthreereviewers,36paperswereaccepted,fromwhich22wereselected for oral presentation and 14 as posters. These contributions were regrouped into topics: applications, discrete topology, discrete hierarchical geometry, discrete tomography, object properties, recognition, and reconstruction, uncertain ge- etry, and visualization.

A Versatile Framework for Handling Subdivided Geometric ObjectsCombinatorial Maps: Efficient Data Structures for Computer Graphics and Image Processing gathers important ideas related to combinatorial maps and explains how the maps are applied in geometric modeling and image processing. It focuses on two subclasses of combinatorial maps: n-Gmaps and n-maps.Suitable for researchers and graduate students in geometric modeling, computational and discrete geometry, computer graphics, and image processing and analysis, the book presents the data structures, operations, and algorithms that are useful in handling subdivided geometric objects. It shows how to study data structures for the explicit representation of subdivided geometric objects and describes operations for handling the structures. The book also illustrates results of the design of data structures and operations.

A Versatile Framework for Handling Subdivided Geometric ObjectsCombinatorial Maps: Efficient Data Structures for Computer Graphics and Image Processing gathers important ideas related to combinatorial maps and explains how the maps are applied in geometric modeling and image processing. It focuses on two subclasses of combinatorial maps: n-Gmaps an

A Versatile Framework for Handling Subdivided Geometric ObjectsCombinatorial Maps: Efficient Data Structures for Computer Graphics and Image Processing gathers important ideas related to combinatorial maps and explains how the maps are applied in geometric modeling and image processing. It focuses on two subclasses of combinatorial maps: n-Gmaps and n-maps.Suitable for researchers and graduate students in geometric modeling, computational and discrete geometry, computer graphics, and image processing and analysis, the book presents the data structures, operations, and algorithms that are useful in handling subdivided geometric objects. It shows how to study data structures for the explicit representation of subdivided geometric objects and describes operations for handling the structures. The book also illustrates results of the design of data structures and operations.

A Versatile Framework for Handling Subdivided Geometric ObjectsCombinatorial Maps: Efficient Data Structures for Computer Graphics and Image Processing gathers important ideas related to combinatorial maps and explains how the maps are applied in geometric modeling and image processing. It focuses on two subclasses of combinatorial maps: n-Gmaps an

In 2005, the twelfth edition of the conference Discrete Geometry for Computer Imagery was held in Poitiers, France, April 13-15, 2005. The conference was organized by the laboratory SIC ("Signal, Image, Communications") of the University of Poitiers, Centre National de la Recherche Scienti?que and the Technical Committee 18 of the International Association for Pattern Recog- tion. DGCI 2005 was sponsored by the Faculty of Science, the University of Poitiers, the Conseil G' en' eral de la Vienne and the Region of Poitou-Charentes. The aim of the conference was to present recent advances in both theoretical aspects and applications in discrete geometry. This year's conference was organized in combination with the 5th Workshop B on Graph- ased Representations in Pattern Recognition,April 11-13, 2005 also organizedinPoitiers.TheworkshopGbRaimsatusinggraph-basedstructuresin image analysis. There is a strong connection between the community interested in the GbR workshop and the discrete geometry community. For this reason, for the?rsttime,boththeworkshopandtheDGCIconferencewereorganizedin the same place, with a common session of four papers, two submitted to GbR and two to DGCI.The DGCI conference attracted again for this edition many excellent papers, with 53 submitted papers from 21 countries. After careful reviewing by two and sometimesthreereviewers,36paperswereaccepted,fromwhich22wereselected for oral presentation and 14 as posters. These contributions were regrouped into topics: applications, discrete topology, discrete hierarchical geometry, discrete tomography, object properties, recognition, and reconstruction, uncertain ge- etry, and visualization.