Mathematical morphology (MM) is a theory for the analysis of spatial structures. It is called morphology since it aims at analysing 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, etc.
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 forty-five contributions classified by subject. It demonstrates a wide range of topics suited to the morphological approach.
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Theory.- Set operator decomposition and conditionally translation
invariant elementary operators.- Mutational equations of morphological
dilation tubes.- Thresholdings, umbrae, residuals, and surpluses of
l-images.- Filtering.- Adaptive parameterized openings.- Synthesis of
adaptive weighted order statistic filters with gradient algorithms.- A
spatially variant, locally adaptive, background normalization operator.-
Using genetic algorithms in the design of morphological filters.- Minimal
generator basis of a finite structural opening.- Segmentation.- Watershed,
hierarchical segmentation and waterfall algorithm.- Minimum spanning forests
for morphological segmentation.- The flat zone approach and color images.-
Joint region and motion estimation with morphological tools.- Morphological
segmentation of image sequences.- Sampling.- Critical morphological sampling
and applications to image coding.- A sampling approach based on
equicontinuity.- Coding.- Application of morphological filters for contour
image sequence coding.- The geodesic morphological skeleton and fast
transformation algorithms.- Multiparameter skeleton decomposition.-
Representations and slope transform.- Morphological systems theory: slope
transforms, MaxMin differential equations, envelope filters, and sampling.-
Two dual representations of morphology based on the parallel normal transport
property.- Dominance and incidence structures with applications to stochastic
geometry and mathematical morphology.- Granulometries and shape description.-
The multiscale morphology decomposition theorem.- Statistical pattern
spectrum for binary pattern recognition.- Generalized geodesic distances
applied to interpolation and shape description.- Random models and
tessellations.- Performance analysis of amorphological Voronoï tessellation
algorithm.- Optimization in Voronoï diagrams.- A stochastic tessellation of
digital space.- Liquid phase sintered materials modelling by random closed
sets.- Monte-Carlo estimation of morphological granulometric discrete size
distributions.- Algorithmic techniques.- On the implementation of
morphological operations.- An evaluation of priority queues for mathematical
morphology.- One pixel thick skeletons.- Fast grayscale granulometry
algorithms.- An efficient implementation technique of adaptive morphological
operations.- Implementation of a distributed watershed algorithm.-
Visualization of Minkowski operations by computer graphics techniques.-
Morphogenesis simulations with lattice gas.- Biological applications.- Single
object geometry the stereology of registered serial sections.- Texture
classification using neural networks and local granulometries.- Fusion of MR
and CT images of the human brain using multiresolution morphology.-
Morphological scheme for morphometric analysis of epidermal biopsy images.-
Automatic quantification of spine parameters from Xray images by means of
morphological tools.- Industrial and remote sensing applications.- Image
Processing: a key to success in industrial applications.- Radar images
analysis using morphological filters.- Application of morphological operators
to supervised multidimensional data classification.- Appendix A.- The Centre
de Morphologie Mathémathique: an overview.- Appendix B.- List of posters
contributions presented at ISMM94.- Author Index.
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