Titlebook: Discrete Geometry for Computer Imagery; 6th International Wo Serge Miguet,Annick Montanvert,Stéphane Ubéda Conference proceedings 1996 Spri

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书目名称Discrete Geometry for Computer Imagery影响因子(影响力)




书目名称Discrete Geometry for Computer Imagery影响因子(影响力)学科排名




书目名称Discrete Geometry for Computer Imagery网络公开度




书目名称Discrete Geometry for Computer Imagery网络公开度学科排名




书目名称Discrete Geometry for Computer Imagery被引频次




书目名称Discrete Geometry for Computer Imagery被引频次学科排名




书目名称Discrete Geometry for Computer Imagery年度引用




书目名称Discrete Geometry for Computer Imagery年度引用学科排名




书目名称Discrete Geometry for Computer Imagery读者反馈




书目名称Discrete Geometry for Computer Imagery读者反馈学科排名

合群

Fast computation of the normal vector field of the surface of a 3-D discrete object,rete object at a given scale. Its time cost is proportional to the number of surfels at and little dependent on the scale. We prove that our algorithm converges toward the right value in the case of a plane surface. We also give some experimental results on families of curved surfaces.

要控制

Hypergraph model of digital topology for grey level images,images..The model is based on the fundamental Helly property of Hypergraphs. This paper introduces the Helly filter which gives to the neighborhood hypergraph associated with an image, the Helly property. As an application example, the model is successfully used to build a segmentation process.

通便

0302-9743 between theory and practice. The issues addressed are topology, geometry, shape representation, 3D surfaces and volumes, models for discrete space, image transformation and generation.978-3-540-62005-1978-3-540-49595-6Series ISSN 0302-9743 Series E-ISSN 1611-3349

Commentary

0302-9743 Lyon, France, in November 1996..Computer imaging essentially depends on discrete models for coding, processing, recognition, representation, etc. The volume presents 24 revised full papers selected from 41 submissions together with 3 invited contributions and a tutorial paper, which bridges the gap

通情达理

通情达理

asthma

永久

芳香一点

Least squares fitting of digital polynomial segments,als is assumed. One of such representations is (.., m, a., a.−1,..., ..), where .. and . are the .-coordinate of the left endpoint and the number of digital points, respectively, while .., ..−1,..., .. are the coefficients of the least squares polynomial fit ..X.+a.X.+ ...+a., for a given digital polynomial segment.