Cover image for Digital Geometry : Geometric Methods for Digital Picture Analysis.
Digital Geometry : Geometric Methods for Digital Picture Analysis.
Title:
Digital Geometry : Geometric Methods for Digital Picture Analysis.
Author:
Klette, Reinhard.
ISBN:
9780080477268
Personal Author:
Physical Description:
1 online resource (675 pages)
Series:
The Morgan Kaufmann Series in Computer Graphics
Contents:
Preface -- Structure of this Book -- Contents -- 1. Introduction -- 1.1 Pictures -- 1.1.1 Pixels, voxels, and their values -- 1.1.2 Picture resolution and picture size -- 1.1.3 Scan orders -- 1.1.4 Adjacency and connectedness -- 1.2 Digital Geometry and Related Disciplines -- 1.2.1 Coordinates and metric spaces -- 1.2.2 Euclidean, similarity, and affine geometry -- 1.2.3 Projective geometry -- 1.2.4 Vector and geometric algebra -- 1.2.5 Graph theory -- 1.2.6 Topology -- 1.2.7 Approximation and estimation -- 1.2.8 Combinatorial geometry -- 1.2.9 Computational geometry -- 1.2.10 Fuzzy geometry -- 1.2.11 Integral geometry, isoperimetry, stereology, and tomography -- 1.2.12 Mathematic morphology -- 1.3 Exercises -- 1.4 Commented Bibliography -- 2. Grids and Digitization -- 2.1 The Grid Point and Grid Cell Models -- 2.1.1 Grid points and grid cells -- 2.1.2 Variable grid resolution -- 2.1.3 Adjacencies in 2D grids -- 2.1.4 Adjacencies in 3D grids -- 2.1.5 Grid cell incidence -- 2.2 Connected Components -- 2.2.1 Connectedness and components -- 2.2.2 Counting connected sets -- 2.2.3 Component labeling -- 2.3 Digitization Models -- 2.3.1 Gauss digitization -- 2.3.2 Jordan digitization -- 2.3.3 Grid-intersection digitization -- 2.3.4 Types of digital sets -- 2.3.5 Domain digitizations -- 2.4 Property Estimation -- 2.4.1 Content estimation -- 2.4.2 Convergent 2D area estimates -- 2.4.3 Multigrid convergence -- 2.5 Exercises -- 2.6 Commented Bibliography -- 3. Metrics -- 3.1 Basics About Metrics -- 3.1.1 The Euclidean metric -- 3.1.2 Norms and Minkowski metrics -- 3.1.3 Scalar products and angles -- 3.1.4 Integer-Valued metrics -- 3.1.5 Restricting and combining metrics -- 3.1.6 Boundedness -- 3.1.7 The topology induced by a metric -- 3.1.8 Distances between sets -- 3.2 Grid Point Metrics -- 3.2.1 Basic grid point metrics.

3.2.2 Neighborhoods and degrees of closeness -- 3.2.3 Approximations to the Euclidean metric -- 3.2.4 Paths, geodesics, and intrinsic distances -- 3.2.5 Distances between sets -- 3.3 Grid Cell Metrics -- 3.3.1 Basic grid cell metrics -- 3.3.2 Seminorms -- 3.3.3 Scalar products and angles -- 3.4 Metrics on Pictures -- 3.4.1 Value-weighted distance -- 3.4.2 Distance transforms -- 3.4.3 The Euclidean distance transform -- 3.4.4 Medial axes -- 3.5 Exercises -- 3.6 Commented Bibliography -- 4. Adjacency Graphs -- 4.1 Graphs, Adjacency Structures, and Adjacency Graphs -- 4.1.1 Graphs and adjacency structures -- 4.1.2 Connectedness with respect to a subgraph -- 4.1.3 Adjacency graphs -- 4.1.4 Types of nodes -- region adjacencies -- 4.2 Some Basics of Graph Theory -- 4.2.1 Nodes, paths, and distances -- 4.2.2 Special types of nodes, edges, and graphs -- 4.3 Oriented Adjacency Graphs -- 4.3.1 Local circular orders -- 4.3.2 The Euler characteristic and planarity -- 4.3.3 Atomic and border cycles -- 4.3.4 The separation theorem -- 4.3.5 Holes -- 4.3.6 Boundaries -- 4.3.7 Some combinatorial results -- 4.4 Combinatorial Maps -- 4.4.1 2D maps -- 4.4.2 3D maps -- 4.5 Exercises -- 4.6 Commented Bibliography -- 5. Incidence Pseudographs -- 5.1 Incidence Structures -- 5.1.1 Adjacency and completeness -- incidence pseudographs -- 5.1.2 Incidence grids -- 5.1.3 Components and regions -- borders -- 5.1.4 Closed and open regions -- 5.2 Boundaries, Frontiers, and the Euler Characteristic -- 5.2.1 Boundaries, chains, and frontiers -- 5.2.2 The matching theorem -- 5.2.3 The Euler characteristic -- 5.3 The Regular Case -- 5.3.1 Regular infinite incidence pseudographs -- 5.3.2 The region matching theorem -- 5.3.3 Euler characteristics -- 5.4 Pictures on Incidence Grids -- 5.4.1 Ordered labeling -- 5.4.2 The ordered adjacency procedure -- 5.4.3 Frontiers in 2D incidence grids.

5.4.4 Frontiers in 3D incidence grids -- 5.5 Exercises -- 5.6 Commented Bibliography -- 6. Topology -- 6.1 Topologic Spaces -- 6.1.1 General definitions -- 6.1.2 Poset topologies -- 6.1.3 Topologies on incidence pseudographs -- 6.2 Digital Topologies -- 6.2.1 General definition -- 6.2.2 The grid point topology -- 6.2.3 The grid cell topology -- 6.2.4 The number of digital topologies -- 6.2.5 Topologic adjacency and dimension -- 6.3 Topologic Concepts -- 6.3.1 Homeomorphy -- 6.3.2 Isotopy -- 6.3.3 Homotopy -- 6.4 Combinatorial Topology -- 6.4.1 Geometric complexes and the Euler characteristic -- 6.4.2 Euclidean complexes -- 6.4.3 Simplicial complexes -- triangulations -- 6.4.4 Abstract complexes -- 6.4.5 The Poincaré formula -- 6.4.6 Homology groups -- 6.5 Exercises -- 6.6 Commented Bibliography -- 7. Curves and Surfaces: Topology -- 7.1 Curves in the Euclidean Topology -- Jordan curves -- Urysohn-Menger curves -- Simple curves and arcs -- Elementary curves and the Euler characteristic -- Separation theorems -- 7.2 Curves in Incidence Grids -- Frontier grids -- curves of marginal nodes -- Curves of principal nodes -- 7.3 Curves in Adjacency Grids -- Euler characteristics of curves -- Simple 2D curves -- Good pairs for 2D binary pictures -- s-Adjacencies in 2D multivalued pictures -- 7.4 Surfaces in the Euclidean Topology -- Manifolds -- Surfaces -- Orientable surfaces -- The connectivity and genus of a surface -- Separation theorems -- 7.5 Surfaces and Separations in 3D Grids -- Surfaces in the grid point model -- Surfaces in the grid cell topology -- Separations in adjacency grids -- 7.6 Exercises -- 7.7 Commented Bibliography -- 8. Curves and Surfaces: Geometry -- 8.1 Planar Curves and Arcs -- 8.2 Space Curves and Arcs -- 8.3 Surfaces and Solids -- 8.4 Surface Tracing and Approximation -- 8.5 Exercises -- 8.6 Commented Bibliography.

9. 2D Straightness -- 9.1 Basics -- 9.2 Supporting Lines -- 9.3 Self-Similarity -- 9.3.1 The chord property -- 9.3.2 Syntactic characterization -- 9.3.3 Continued fractions -- 9.4 Periodicity -- 9.5 Number-Theoretic Properties -- 9.5.1 Counting segments and partitions -- 9.5.2 Spirographs -- 9.6 Algorithms -- 9.6.1 Design paradigms -- 9.6.2 A linear online DSS recognition algorithm -- 9.6.3 Review of other algorithms -- 9.6.4 A linear online 4-DSS algorithm -- 9.7 Exercises -- 9.8 Commented Bibliography -- 10. 2D Arc Length -- Curvature and Corners -- 10.1 The Length of a Digital Curve -- 10.1.1 Curve digitizations -- 10.1.2 Local and global estimation -- 10.1.3 DSS-based estimation -- 10.1.4 MLP-based estimation -- 10.1.5 Tangent-based estimation -- 10.2 Definitions of 2D Arc Length Estimators -- 10.2.1 Local estimators -- 10.2.2 DSS estimators -- 10.2.3 MLP estimators -- 10.2.4 MLPs of simple 1-curves -- 10.2.5 The approximating sausage approach -- 10.2.6 Tangent-based estimators -- 10.3 Evaluation of 2D Arc Length Estimators -- 10.3.1 Online and offline algorithms and time complexity -- 10.3.2 Multigrid convergence theorems -- 10.3.3 Proof of Theorem 10.1 -- 10.3.4 Experimental evaluation -- 10.4 The Curvature of a Planar Digital Curve -- 10.4.1 Corner detectors -- 10.4.2 Curvature estimators -- 10.4.3 Experimental evaluation -- 10.5 Exercises -- 10.6 Commented Bibliography -- 11. 3D Straightness and Planarity -- 11.1 3D Straightness -- 11.1.1 Grid-plane intersection digitization -- 11.1.2 Arithmetic geometry -- 11.1.3 A linear online 3D DSS segmentation algorithm -- 11.1.4 MLPs of simple 2-curves -- 11.1.5 The rubber band algorithm -- 11.2 Digital Planes in 3D Adjacency Grids -- 11.2.1 3D grid-line intersection digitization -- 11.2.2 Self-similarity -- 11.2.3 Supporting and separating planes -- 11.2.4 Arithmetic planes -- 11.2.5 Periodicity.

11.2.6 Connectivity of arithmetic planes -- 11.3 Digital Planes in the 3D Incidence Grid -- 11.4 DPS Recognition and Generation -- 11.4.1 An incremental DPS algorithm -- 11.4.2 DPS generation algorithms -- 11.5 Exercises -- 11.6 Commented Bibliography -- 12. 3D Arc Length, Surface Area, and Curvature -- 12.1 3D Arcs -- 12.1.1 Arc length estimation -- 12.1.2 Estimation of curvature and torsion -- 12.2 Surface Area Estimation -- 12.2.1 Local methods -- 12.2.2 RCH methods -- 12.2.3 NOR methods -- 12.2.4 DPS methods -- 12.3 Surface Curvature Estimation -- 12.4 Exercises -- 12.5 Commented Bibliography -- 13. Hulls and Diagrams -- 13.1 Hulls -- 13.1.1 Convex hull computation in the Euclidean plane -- 13.1.2 Convex hull computation in the (2D) grid -- 13.1.3 Near-hull computation in the Euclidean plane -- 13.2 2D Digital Convexity -- 13.2.1 Digital convex hulls -- 13.2.2 Row and column convexity -- 13.2.3 Fuzzy digital convexity -- 13.3 Diagrams -- 13.3.1 Diagram computation in the Euclidean plane -- 13.3.2 Diagram computation in the digital plane -- 13.3.3 Diagrams in pictures -- 13.4 Exercises -- 13.5 Commented Bibliography -- 14. Transformations -- 14.1 Geometries -- 14.2 Axiomatic Digital Geometry -- 14.3 Transformation Groups and Symmetries -- 14.4 Neighborhood-Preserving Transformations -- 14.5 Applying Transformations to Pictures -- 14.6 Magnification and Demagnification -- 14.7 Digital Tomography -- 14.8 Exercises -- 14.9 Commented Bibliography -- 15. Morphologic Operations -- 15.1 Dilation -- 15.2 Erosion -- 15.3 Combining Dilations and Erosions -- 15.3.1 Hit-and-miss transforms and templates -- 15.3.2 Opening and closing -- 15.4 Simplification -- 15.5 Segmentation -- 15.5.1 Thresholding -- 15.5.2 Local features -- 15.5.3 Texture -- 15.6 Decomposition -- 15.6.1 Clusters -- 15.6.2 Elongated object parts -- 15.6.3 Distance transforms and medial axes.

15.7 Exercises.
Abstract:
Digital geometry is about deriving geometric information from digital pictures. The field emerged from its mathematical roots some forty-years ago through work in computer-based imaging, and it is used today in many fields, such as digital image processing and analysis (with applications in medical imaging, pattern recognition, and robotics) and of course computer graphics. Digital Geometry is the first book to detail the concepts, algorithms, and practices of the discipline. This comphrehensive text and reference provides an introduction to the mathematical foundations of digital geometry, some of which date back to ancient times, and also discusses the key processes involved, such as geometric algorithms as well as operations on pictures. *A comprehensive text and reference written by pioneers in digital geometry, image processing and analysis, and computer vision *Provides a collection of state-of-the-art algorithms for a wide variety of geometrical picture analysis tasks, including extracting data from digital images and making geometric measurements on the data *Includes exercises, examples, and references to related or more advanced work.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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