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Mathematical Morphology and Its Applications to Image and Signal Processing

By: Jean Serra (Editor), Pierre Soille (Editor)

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Hardcover
396 Pages

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23.39 x 15.6 x 2.24

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Mathematical morphology (MM) is a theory for the analysis of spatial structures. It is called morphology since it aims at analyzing the shape and form of objects, and it is mathematical in the sense that the analysis is based on set theory, topology, lattice algebra, random functions, and so on. MM is not only a "theory", but also a powerful image analysis "technique". The purpose of the present book is to provide the image analysis community with a snapshot of current theoretical and applied developments of MM. The book consists of 45 contributions classified by subject. It demonstrates a range of topics suited to the morphological approach.

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You Can Find This Book In

Non-Fiction Computing & I.T.Computer Science Image Processing Engineering & Technology Other Technologies & Applied Sciences Applied Optics Artificial Intelligence Computer Vision Mathematics Algebra Medicine

Other Branches of Medicine Medical Imaging Graphical & Digital Media Applications

Preface
Introduction
Set operator decomposition and conditionally translation invariant elementary operators	p. 5
Mutational equations of morphological dilation tubes	p. 13
Thresholdings, umbrae, residuals, and surpluses of l-images	p. 21
Adaptive parameterized openings	p. 29
Synthesis of adaptive weighted order statistic filters with gradient algorithms	p. 37
A spatially variant, locally adaptive, background normalization operator	p. 45
Using genetic algorithms in the design of morphological filters	p. 53
Minimal generator basis of a finite structural opening	p. 61
Watershed, hierarchical segmentation and waterfall algorithm	p. 69
Minimum spanning forests for morphological segmentation	p. 77
The flat zone approach and color images	p. 85
Joint region and motion estimation with morphological tools	p. 93
Morphological segmentation of image sequences	p. 101
Critical morphological sampling and applications to image coding	p. 109
A sampling approach based on equicontinuity	p. 117
Application of morphological filters for contour image sequence coding	p. 125
The geodesic morphological skeleton and fast transformation algorithms	p. 133
Multi-parameter skeleton decomposition	p. 141
Morphological systems theory: slope transforms, Max-Min differential equations, envelope filters, and sampling	p. 149
Two dual representations of morphology based on the parallel normal transport property	p. 161
Dominance and incidence structures with applications to stochastic geometry and mathematical morphology	p. 171
The multiscale morphology decomposition theorem	p. 179
Statistical pattern spectrum for binary pattern recognition	p. 185
Generalized geodesic distances applied to interpolation and shape description	p. 193
Performance analysis of a morphological Voronoi tessellation algorithm	p. 201
Optimization in Voronoi diagrams	p. 209
A stochastic tessellation of digital space	p. 217
Liquid phase sintered materials modelling by random closed sets	p. 225
Monte-Carlo estimation of morphological granulometric discrete size distributions	p. 233
On the implementation of morphological operations	p. 241
An evaluation of priority queues for mathematical morphology	p. 249
One pixel thick skeletons	p. 257
Fast grayscale granulometry algorithms	p. 265
An efficient implementation technique of adaptive morphological operations	p. 273
Implementation of a distributed watershed algorithm	p. 281
Visualization of Minkowski operations by computer graphics techniques	p. 289
Morphogenesis simulations with lattice gas	p. 297
Single object geometry - the stereology of registered serial sections	p. 305
Texture classification using neural networks and local granulometries	p. 309
Fusion of MR and CT images of the human brain using multiresolution morphology	p. 317
Morphological scheme for morphometric analysis of epidermal biopsy images	p. 325
Automatic quantification of spine parameters from X-ray images by means of morphological tools	p. 333
Image Processing: a key to success in industrial applications	p. 341
Radar images analysis using morphological filters	p. 353
Application of morphological operators to supervised multidimensional data classification	p. 361
Appendix A: The "Centre de Morphologie Mathemathique": an overview	p. 369
Appendix B: List of posters contributions presented at ISMM'94	p. 375
Author Index	p. 377
Subject Index	p. 379
Table of Contents provided by Blackwell. All Rights Reserved.

Mathematical Morphology and Its Applications to Image and Signal Processing

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Hardcover

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