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Banon G.J.F., Barrera J., Braga-Neto U.M. (eds.) Mathematical Morphology and its Applications to Signal and Image Processing

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Banon G.J.F., Barrera J., Braga-Neto U.M. (eds.) Mathematical Morphology and its Applications to Signal and Image Processing
Science & Technogy Ministry of Brasil, 2007 -546 pp.
Proceedings of the 8th International Symposium on Mathematical Morphology, Rio de Janeiro, RJ, Brazil, October 10-13, 2007.
Mathematical Morphology (MM) was created in the mid-sixties by a group led by Georges Matheron and Jean Serra of the Paris School of Mines in Fontainebleau, France. By the end of the seventies, its usefulness for image analysis had been recognized in Europe, in particular within the area of microscopic imaging. Starting in the eighties, with the publication in English of Serra's books on Image Analysis and Mathematical Morphology, MM spread worldwide. In 1993, the MM community organized the first International Symposium on Mathematical Morphology (ISMM), an event that has been held approximately biennially ever since.
Part I Lattice theory
An extension of skeleton by influence zones and morphological interpolation to fuzzy sets
Basis Computation Algorithms
Division of mappings between complete lattices
General approach for fuzzy mathematical morphology
Self-dual morphology on tree semilattices and applications
Part II Geometry and topology
Locally finite spaces and the join operator
Digital Steiner sets and Matheron semi-groups
The random spread model
Part III Signal processing
A scale-space toggle operator for morphological segmentation
Comparing morphological levelings constrained by different markers
Leveling cartoons, texture energy markers, and image decomposition
Part IV Image processing
A new shape descriptor based on tensor scale
On morphological color texture characterization
Micro-viscous morphological operators
Scene text localization based on the ultimate opening
News from viscousland
A region-based interpolation method for mosaic images
Part V Connectivity
Adjacency stable connected operators and set levelings
Perceptual filtering with connected operators and image inpainting
Segmentation using vector-attribute filters: methodology and application to dermatological imaging
Part VI Watershed segmentation
Some links between min-cuts, optimal spanning forests and watersheds
Stochastic watershed segmentation
Watershed by image foresting transform, tie-zone, and theoretical relationships with other watershed definitions
Watershed-based visualization of high-density EEG coherence
Watershed cuts
Watershed from propagated markers improved by a marker binding heuristic
Two approaches for orientation field segmentation based on directional morphology
Design of robust pattern classifiers based on optimum-path forests
Computing approximate geodesics and minimal surfaces using watershed and graph-cuts
Part VII Texture and geometrical segmentation
Morphological texture gradients: Definition and application to colour and texture watershed segmentation
Oversegmentation control for inexact graph matching: First results
Segmentation of random textures by morphological and linear operators
On distances, paths and connections for hyperspectral image segmentation
Generalized watershed and PDEs for geometric-textural segmentation
Part VIII Algorithms and architectures
A partitioned algorithm for the image foresting transform
1D Component tree in linear time and space and its application to gray-level image multithresholding
A parallel implementation of the dual-input Max-Tree algorithm for attribute filtering
Multi-level decomposition of Euclidean spheres
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