Image Processing

Dealing with Texture

Maria Petrou, Pedro Garcia Sevilla

640 pages, parution le 05/04/2006

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Résumé

Self-contained text covering practical image processing methods and theory for image texture analysis.

Techniques for the analysis of texture in digital images are essential to a range of applications in areas as diverse as robotics, defence, medicine and the geo-sciences. In biological vision, texture is an important cue allowing humans to discriminate objects. This is because the brain is able to decipher important variations in data at scales smaller than those of the viewed objects. In order to deal with texture in digital data, many techniques have been developed by image processing researchers.

With a wholly practical approach and many worked examples, Image Processing: Dealing with Texture is a comprehensive guide to these techniques, including chapters on mathematical morphology, fractals, Markov random fields, Gabor functions and wavelets. Structured around a series of questions and answers, enabling readers to easily locate information on specific problems, this book also:

provides detailed descriptions of methods used to analyse binary as well as grey texture images
presents information on two levels: an easy-to-follow narrative explaining the basics, and an advanced, in-depth study of mathematical theorems and concepts
looks at 'good' and 'bad' image processing practice, with wrongly designed algorithms illustrating 'what not to do'
includes an accompanying website, setting out all algorithms discussed within the text.

An ideal self-teaching aid for senior undergraduate and Masters students taking courses in image processing and pattern recognition, this book is also an ideal reference for PhD students, electrical and biomedical engineers, mathematicians, and informatics researchers designing image processing applications.

Sommaire

Introduction
Binary textures
- Shape grammars
- Boolean models
- Mathematical morphology
Stationary grey texture images 81
- Image binarisation
- Grey scale mathematical morphology
- Fractals
- Markov random fields
- Gibbs distributions
- The autocorrelation function as a texture descriptor
- Texture features from the Fourier transform
- Co-occurrence matrices
Non-stationary grey texture images
- The uncertainty principle and its implications in signal and image processing
- Gabor functions
- Prolate spheroidal sequence functions
- Wavelets
- Where Image Processing and Pattern Recognition meet
- Laws' masks and the what looks like where space
- Local binary patterns
- The Wigner distribution

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Auteur(s)	Maria Petrou, Pedro Garcia Sevilla
Parution	05/04/2006
Nb. de pages	640
Format	17 x 25
Couverture	Relié
Poids	1310g
Intérieur	Noir et Blanc
EAN13	9780470026281
ISBN13	978-0-470-02628-1