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Finance
Genetics
Image Analysis: Mathematical morphology
TODO
The structure of this section could be: - Microarrays, gene clustering (SOM) - Phylogenetics - QTL I could mention the following packages: qtl (quantitative traits loci) bqtl GeneSOM Clustering genes using Self-Organizing Maps (SOMs). ape Analyses of Phylogenetics and Evolution sma micro-array analysis permax (DNA array) genetics PHYLOGR (devel) See also the Bioconductor, that mainly focuses on DNA microarrays. http://www.bioconductor.org/packages/devel/html/
"Mathematical morphology" refers to local image transformation algorithms -- "local" means that the new colour of a pixel depends on that of the neighbouring pixels.
For instance, the game of life is local transformation.
TODO: Explain, insert a few plots.
(The more rigorous definition, should you want it, refers to non-decreasing, involutive and local transformations.)
Introduction: explain what mathematical morphology is.
Give a few examples of images one could want to process.
http://www.mmorph.com/pymorph/
http://www.ensta.fr/~manzaner/Publis/These.ps.gz
morphology.R
http://zoonek.free.fr/Ecrits/2004_BioRet.pdf.bz2
Images (plot.image, plot3d.image)
Packages: mainly EBImage, but also rimage, pixmap
Basic operations:
translations
rotations
Structuring elements (plot.structuring.element)
Hit-and-Miss transform ("pattern matching")
Intersection (inf), union (sup), complementary, difference
Dilatation, Erosion
Opening, closing
Gradient, internal gradient, external gradient, laplacian
Top hat
Reconstruction: Hysteresis threshold, Hole filling
Local maxima, max.loc.hys,
regional maxima, geodesic dilatation, r.h.maxima
skeleton, hairy or not
Homotopic kernel (median axis)
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
Vincent Zoonekynd
<zoonek@math.jussieu.fr>
latest modification on Sat Jan 6 10:28:26 GMT 2007