Difference between revisions of "TheoExtraStuff"

From LRDE

(Lectures)
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* Introduction to Image Processing (slides: [http://www.lrde.epita.fr/~theo/lectures/INIM/inim_1.pdf inim_1.pdf], [http://www.lrde.epita.fr/~theo/lectures/INIM/inim_2.pdf inim_2.pdf], [http://www.lrde.epita.fr/~theo/lectures/INIM/inim_3.pdf inim_3.pdf], [http://www.lrde.epita.fr/~theo/lectures/INIM/inim_4.pdf inim_4.pdf], [http://www.lrde.epita.fr/~theo/lectures/INIM/inim_5.pdf inim_5.pdf])
 
* Introduction to Image Processing (slides: [http://www.lrde.epita.fr/~theo/lectures/INIM/inim_1.pdf inim_1.pdf], [http://www.lrde.epita.fr/~theo/lectures/INIM/inim_2.pdf inim_2.pdf], [http://www.lrde.epita.fr/~theo/lectures/INIM/inim_3.pdf inim_3.pdf], [http://www.lrde.epita.fr/~theo/lectures/INIM/inim_4.pdf inim_4.pdf], [http://www.lrde.epita.fr/~theo/lectures/INIM/inim_5.pdf inim_5.pdf])
 
* Markov Random Fields
 
* Markov Random Fields
  +
   
 
== Students ==
 
== Students ==

Revision as of 09:08, 9 October 2014



Back to my homepage <--


Software Snapshots

a modern, efficient, and generic image processing library in C++, Milena, part of the Olena platform:

  • the main project page is here
  • I'm ranked by Ohloh (!) here


Lectures

The courses I give at EPITA:


Students

Former PhD students:

Current PhD students:


Internship Proposals

The proposal below are for MSc students (M2); if you are interested (and to get extra info), just contact me thierry.geraud@lrde.epita.fr.

Text extraction from natural images

Keywords
  • image processing,
  • mathematical morphology,
  • tree-based reasoning,
  • algorithmic optimization.
Flavor
theory 10%
bibliography 10%
exploration 30%
algorithm design 30%
implementation and tests 20%

Exploration of new self-dual filters in mathematical morphology

Keywords
Flavor
theory 20%
bibliography 10%
exploration 30%
proof design 30%
implementation and tests 10%

Document image simplification

Keywords
  • image processing,
  • mathematical morphology,
  • tree-based reasoning,
  • algorithmic optimization.

Keywords:

  • image processing,
  • mathematical morphology,
  • document image analysis.
Flavor
theory 10%
bibliography 20%
exploration 40%
implementation and tests 30%