Digital Geometry,
Edition 1 Geometric Methods for Digital Picture Analysis
By Reinhard Klette and Azriel Rosenfeld

Publication Date: 06 Aug 2004
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.

Key Features

*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
About the author
By Reinhard Klette, The University of Auckland, New Zealand; and Azriel Rosenfeld, University of Maryland, College Park, U.S.A.
Table of Contents
Introduction. Grids and Digitization. Metrics. Adjacency Graphs. Incidence Pseudographs. Topology: Basics. Curves and Surfaces: Topology. Curves and Surfaces: Geometry. Straightness. Arc Length and Curvature. 3D Straightness and Planarity. Surface and Area Curvature. Hulls and Diagrams. Transformations. Morphological Operations. Deformations. Other Properties and Relations. Bibliography.
Book details
ISBN: 9781558608610
Page Count: 672
Illustrations : Approx. 400 illustrations
Retail Price : £69.99
Gonzalez, et al.: Digital Image Processing 2E ($115/£68, 2002, 0201180758)
Those who want to extract information from digital images for work and personal applications, and researchers and students in digital image processing, computer vision, and computer graphics.