
Markov Point Processes And Their Applications
Marie-Colette van Lieshout(Author)
Imperial College Press
Published on 13. July 2000
Book
Hardback
184 pages
978-1-86094-071-2 (ISBN)
Description
These days, an increasing amount of information can be obtained in graphical forms, such as weather maps, soil samples, locations of nests in a breeding colony, microscopical slices, satellite images, radar or medical scans and X-ray techniques. "High level" image analysis is concerned with the global interpretation of images, attempting to reduce it to a compact description of the salient features of the scene.This book takes a stochastic approach. It studies Markov object processes, showing that they form a flexible class of models for a range of problems involving the interpretation of spatial data. Applications can be found in statistical physics (under the name of "Gibbs processes"), environmental mapping of diseases, forestry, identification of ore structure in materials science, signal analysis, object recognition, robot vision, and interpretation of images from medical scans or confocal microscopy.
Reviews / Votes
"The book is remarkable by the amount of the material covered and excellent readability ... It is highly recommended as the first comprehensive text that covers various concepts related to Markov point processes and typically scattered in the journal literature." Mathematical Reviews, 2001More details
Language
English
Place of publication
London
United Kingdom
Target group
College/higher education
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 223 mm
Width: 158 mm
Thickness: 15 mm
Weight
399 gr
ISBN-13
978-1-86094-071-2 (9781860940712)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Person
Content
Part 1 Point processes: the Poisson process; finite point processes; interior and exterior conditioning. Part 2 Markov point processes: Ripley-Kelly Markov point processes; marked point processes; nearest-neighbour Markov point processes. Part 3 Statistics for Markov point processes: simulation; parameter estimation. Part 4 Applications: modelling of spatial patterns; higher-level vision.