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Image Analysis and Mathematical Morphology
This invaluable reference helps readers assess and simplify problems and their essential requirements and complexities, giving them all the necessary data and methodology to master current theoretical developments and applications, as well as create new ones.
A Lattice Approach to Image Segmentation
  • J. Serra
  • Mathematics, Computer Science
    Journal of Mathematical Imaging and Vision
  • 2005
After a formal definition of segmentation as the largest partition of the space according to a criterion σ and a function f, the notion of a morphological connection is reminded. It is used as an
Flat zones filtering, connected operators, and filters by reconstruction
It is shown that from any connected operator acting on sets, one can construct a connected operator for functions (however, it is not the unique way of generating connected operators for functions).
Connectivity on Complete Lattices
  • J. Serra
  • Computer Science, Mathematics
    Journal of Mathematical Imaging and Vision
  • 1 November 1998
The present paper extends the nontopological axiomatics of connectivity to complete sup-generated lattices, and finds that a connection turns out to be characterized by a family of openings labelled by the sup-generators, which partition each element of the lattice into maximal terms, of zero infima.
Introduction to mathematical morphology
Transformations morphologiques, morphologie euclidienne, erosion et notions derivees, ouvertures et fermetures, amincissements et epaississements
Mathematical Morphology in the HLS Colour Space
A variation of the standard morphological operators which require the choice of an origin are discussed and a new saturationweighted hue order is presented, which takes hue and saturation into account simultaneously.
A 3D-polar Coordinate Colour Representation Suitable for Image Analysis
The processing and analysis of colour images has become an important area of study and application. The representation of the RGB colour space in 3D-polar coordinates (hue, saturation and brightness)
Automatic analysis of DNA microarray images using mathematical morphology
An automatic non-supervised set of algorithms for a fast and accurate spot data extraction from DNA microarrays using morphological operators which are robust to both intensity variation and artefacts are presented.
Hausdorff distances and interpolations