Mathematical Morphology and Its Application to Signal and Image Processing

The 9th ISMM conference covered a very diverse collection of papers, bound together by the central themes of mathematical morphology, namely, the tre- ment of images in terms of set and lattice theory. Notwithstanding this central theme, this ISMM showed increasing interaction with other ?elds of image and signal processing, and several hybrid methods were presented, which combine the strengths of traditional morphological methods with those of, for example, linear ?ltering.This trendis particularlystrong in the emerging?eld of adaptive morphological ?ltering, where the local shape of structuring elements is det- mined by non-morphological techniques. This builds on previous developments of PDE-based methods in morphology and amoebas. In segmentation we see similar advancements, in the development of morphological active contours. Even within morphology itself, diversi?cation is great, and many new areas of research are being opened up. In particular, morphology of graph-based and complex-based image representations are being explored. Likewise, in the we- established area of connected ?ltering we ?nd new theory and new algorithms, but also expansion into the direction of hyperconnected ?lters. New advances in morphological machine learning, multi-valued and fuzzy morphology are also presented. Notwithstanding the often highly theoretical reputation of mathematical morphology, practitioners in this ?eld have always had an eye for the practical.

From the reviews: Mathematical Morphology and its Applications to Signal and Image Processing, edited by M.H.F. Wilkinson and J.B.T.M. Roerdink forms vol. 5720 of Springer's Lecture Notes in Computer Science . if you hope to keep up with mathematical morphology, you will have to read this book. (Ultramicroscopy, Vol. 110, 2010)

Klappentext

This book constitutes the refereed proceedings of the 9th International Symposium on Mathematical Morphology, ISMM 2009 held in Groningen, The Netherlands in August 2009.

The 27 revised full papers presented together with one invited paper were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on theory, connectivity and connected filters, adaptive morphology, graphs and topology, segmentation, shape, morphology of multi-valued images, and algorithms.

Inhalt
Invited Speaker.- Discrete Driver Assistance.- Theory.- The False Colour Problem.- Bipolar Fuzzy Mathematical Morphology for Spatial Reasoning.- An Axiomatic Approach to Hyperconnectivity.- Hyperconnectivity, Attribute-Space Connectivity and Path Openings: Theoretical Relationships.- Connectivity and Connected Filters.- Constrained Connectivity and Transition Regions.- Surface-Area-Based Attribute Filtering in 3D.- Levelings and Geodesic Reconstructions.- A Comparison of Spatial Pattern Spectra.- Adaptive Morphology.- Differential Equations for Morphological Amoebas.- Spatially-Variant Anisotropic Morphological Filters Driven by Gradient Fields.- 3-D Extraction of Fibres from Microtomographic Images of Fibre-Reinforced Composite Materials.- Spatially-Variant Morpho-Hessian Filter: Efficient Implementation and Application.- Graphs and Topology.- Some Morphological Operators in Graph Spaces.- Morphology on Graphs and Minimum Spanning Trees.- Segmentation.- Segmentation of Complex Images Based on Component-Trees: Methodological Tools.- Ultrametric Watersheds.- An Efficient Morphological Active Surface Model for Volumetric Image Segmentation.- Shape.- Ultimate Attribute Opening Segmentation with Shape Information.- Hierarchical Shape Decomposition via Level Sets.- Morphological Exploration of Shape Spaces.- Morphology of Multi-valued Images.- From Scalar-Valued Images to Hypercomplex Representations and Derived Total Orderings for Morphological Operators.- A Directional Rouy-Tourin Scheme for Adaptive Matrix-Valued Morphology.- Component-Trees and Multi-value Images: A Comparative Study.- Algorithms.- Fast Implementation of the Ultimate Opening.- Stack Filter Classifiers.- Milena: Write Generic Morphological Algorithms Once, Run on Many Kinds of Images.- An EfficientAlgorithm for Computing Multi-scale Connectivity Measures.