https://www.lrde.epita.fr/index.php?title=Affiche-these-NB&feed=atom&action=historyAffiche-these-NB - Revision history2024-03-28T23:47:37ZRevision history for this page on the wikiMediaWiki 1.35.3https://www.lrde.epita.fr/index.php?title=Affiche-these-NB&diff=98741&oldid=prevNboutry at 20:40, 19 November 20162016-11-19T20:40:09Z<p></p>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* LACHAUD Jacques-Olivier, Rapporteur, Professeur, Université Savoie Mont Blanc.</div></td>
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</table>Nboutryhttps://www.lrde.epita.fr/index.php?title=Affiche-these-NB&diff=98615&oldid=prevNboutry at 15:12, 18 November 20162016-11-18T15:12:42Z<p></p>
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</table>Nboutryhttps://www.lrde.epita.fr/index.php?title=Affiche-these-NB&diff=98303&oldid=prevNboutry at 17:29, 16 November 20162016-11-16T17:29:12Z<p></p>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Abstract:'''</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>Digitization of the real world using real sensors has many drawbacks; in particular, we loose <del class="diffchange diffchange-inline">``</del>well-composedness<del class="diffchange diffchange-inline">''</del> in the sense that two digitized objects can be connected or not depending on the connectivity we choose in the digital image, leading then to ambiguities. Furthermore, digitized images are arrays of numerical values, and then do not own any topology by nature, contrary to our usual modeling of the real world in mathematics and in physics. Loosing all these properties makes difficult the development of algorithms which are <del class="diffchange diffchange-inline">``</del>topologically correct<del class="diffchange diffchange-inline">''</del> in image processing: e.g., the computation of the tree of shapes needs the representation of a given image to be continuous and well-composed; in the contrary case, we can obtain abnormalities in the final result. Some well-composed continuous representations already exist, but they are not in the same time n-dimensional and self-dual. n-dimensionality is crucial since usual signals are more and more 3-dimensional (like 2D videos) or 4-dimensional (like 4D Computerized Tomography-scans), and self-duality is necessary when a same image can contain different objects with different contrasts. We developed then a new way to make images well-composed by interpolation in a self-dual way and in n-D; followed with a span-based immersion, this interpolation becomes a self-dual continuous well-composed representation of the initial n-D signal. This representation benefits from many strong topological properties: it verifies the intermediate value theorem, the boundaries of any threshold set of the representation are disjoint union of discrete surfaces, and so on.</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>Digitization of the real world using real sensors has many drawbacks; in particular, we loose <ins class="diffchange diffchange-inline">"</ins>well-composedness<ins class="diffchange diffchange-inline">"</ins> in the sense that two digitized objects can be connected or not depending on the connectivity we choose in the digital image, leading then to ambiguities. Furthermore, digitized images are arrays of numerical values, and then do not own any topology by nature, contrary to our usual modeling of the real world in mathematics and in physics. Loosing all these properties makes difficult the development of algorithms which are <ins class="diffchange diffchange-inline">"</ins>topologically correct<ins class="diffchange diffchange-inline">"</ins> in image processing: e.g., the computation of the tree of shapes needs the representation of a given image to be continuous and well-composed; in the contrary case, we can obtain abnormalities in the final result. Some well-composed continuous representations already exist, but they are not in the same time n-dimensional and self-dual. n-dimensionality is crucial since usual signals are more and more 3-dimensional (like 2D videos) or 4-dimensional (like 4D Computerized Tomography-scans), and self-duality is necessary when a same image can contain different objects with different contrasts. We developed then a new way to make images well-composed by interpolation in a self-dual way and in n-D; followed with a span-based immersion, this interpolation becomes a self-dual continuous well-composed representation of the initial n-D signal. This representation benefits from many strong topological properties: it verifies the intermediate value theorem, the boundaries of any threshold set of the representation are disjoint union of discrete surfaces, and so on.</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Keywords: well-composed, discrete surfaces, digital topology, tree of shapes, mathematical morphology.'''</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Keywords: well-composed, discrete surfaces, digital topology, tree of shapes, mathematical morphology.'''</div></td>
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</table>Nboutryhttps://www.lrde.epita.fr/index.php?title=Affiche-these-NB&diff=98302&oldid=prevNboutry: Created page with "{{DISPLAYTITLE:PhD Defense Nicolas Boutry}} <div class="center" style="width: auto; margin-left: auto; margin-right: auto;">126px [[Fil..."2016-11-16T17:27:00Z<p>Created page with "{{DISPLAYTITLE:PhD Defense Nicolas Boutry}} <div class="center" style="width: auto; margin-left: auto; margin-right: auto;"><a href="/wiki/File:Logo_ESIEE_Paris.png" title="File:Logo ESIEE Paris.png">126px</a> [[Fil..."</p>
<p><b>New page</b></p><div>{{DISPLAYTITLE:PhD Defense Nicolas Boutry}}<br />
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<div class="center" style="width: auto; margin-left: auto; margin-right: auto;">[[File:logo_ESIEE_Paris.png|126px]] &nbsp; [[File:logo_LIGM.png|126px]] &nbsp; [[File:Logo EPITA Ingenieur BLEU 3.JPG|126px]] &nbsp; [[File:Lrde.png|126px]] &nbsp; [[File:logo_Université_Paris_Est.jpg|164px]]<br />
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<div class="center" style="width: auto; margin-left: auto; margin-right: auto;"><big>'''SOUTENANCE de THESE'''</big><br />
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<div class="center" style="width: auto; margin-left: auto; margin-right: auto;"><big>'''NICOLAS BOUTRY'''</big><br />
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<div class="center" style="width: auto; margin-left: auto; margin-right: auto;"><big>''' MERCREDI 14 DECEMBRE 2016 '''</big><br />
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<div class="center" style="width: auto; margin-left: auto; margin-right: auto;"><big>''' A 14H00 '''</big><br />
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<div class="center" style="width: auto; margin-left: auto; margin-right: auto;"><big>''' Amphi 110 '''</big><br />
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<div class="center" style="width: auto; margin-left: auto; margin-right: auto;"><big>''' ESIEE, Noisy le Grand '''</big><br />
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<div class="center" style="width: auto; margin-left: auto; margin-right: auto;">Plan d’accès : http://www.esiee.fr/Infos-pratiques/acces.php<br />
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<div class="center" style="width: auto; margin-left: auto; margin-right: auto;"><big>''' A STUDY OF WELL-COMPOSEDNESS IN n-D'''</big><br />
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'''Abstract:'''<br />
<br />
Digitization of the real world using real sensors has many drawbacks; in particular, we loose ``well-composedness'' in the sense that two digitized objects can be connected or not depending on the connectivity we choose in the digital image, leading then to ambiguities. Furthermore, digitized images are arrays of numerical values, and then do not own any topology by nature, contrary to our usual modeling of the real world in mathematics and in physics. Loosing all these properties makes difficult the development of algorithms which are ``topologically correct'' in image processing: e.g., the computation of the tree of shapes needs the representation of a given image to be continuous and well-composed; in the contrary case, we can obtain abnormalities in the final result. Some well-composed continuous representations already exist, but they are not in the same time n-dimensional and self-dual. n-dimensionality is crucial since usual signals are more and more 3-dimensional (like 2D videos) or 4-dimensional (like 4D Computerized Tomography-scans), and self-duality is necessary when a same image can contain different objects with different contrasts. We developed then a new way to make images well-composed by interpolation in a self-dual way and in n-D; followed with a span-based immersion, this interpolation becomes a self-dual continuous well-composed representation of the initial n-D signal. This representation benefits from many strong topological properties: it verifies the intermediate value theorem, the boundaries of any threshold set of the representation are disjoint union of discrete surfaces, and so on.<br />
<br />
'''Keywords: well-composed, discrete surfaces, digital topology, tree of shapes, mathematical morphology.'''<br />
<br />
<br />
'''Composition du Jury :'''<br />
* NAJMAN Laurent , Directeur de thèse, Professeur, ESIEE Paris<br />
* GÉRAUD Thierry, Codirecteur de thèse, Professeur, EPITA<br />
* GONZÁLEZ-DÍAZ Rocio, Rapporteur, Professeure, Universidad de Sevilla,<br />
* PASSAT Nicolas, Professeur, Rapporteur, Université de Reims Champagne-Ardenne,<br />
* LACHAUD Jacques-Olivier, Rapporteur, Professeur, Université Savoie Mont Blanc.<br />
* LATECKI Longin Jan, Examinateur, Professeur, Temple University ,<br />
* MAZO Loïc, Examinateur, Maître de Conférences, Université de Strasbourg,<br />
* COUPRIE Michel, Examinateur, Professeur, ESIEE Paris.</div>Nboutry