Topologically Constrained Segmentation with Topological Maps Alexandre Dupas, Guillaume Damiand To cite this version: Alexandre Dupas, Guillaume Damiand. Topologically Constrained Segmentation with Topological Maps. Workshop on Computational Topology in Image Context, Jun 2008, Poitiers, France. hal- 01517182 HAL Id: hal-01517182 https://hal.archives-ouvertes.fr/hal-01517182 Submitted on 2 May 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Topologically Constrained Segmentation with Topological Maps Alexandre Dupas1 and Guillaume Damiand2 1 XLIM-SIC, Universit´ede Poitiers, UMR CNRS 6172, Bˆatiment SP2MI, F-86962 Futuroscope Chasseneuil, France
[email protected] 2 LaBRI, Universit´ede Bordeaux 1, UMR CNRS 5800, F-33405 Talence, France
[email protected] Abstract This paper presents incremental algorithms used to compute Betti numbers with topological maps. Their implementation, as topological criterion for an existing bottom-up segmentation, is explained and results on artificial images are shown to illustrate the process. Keywords: Topological map, Topological constraint, Betti numbers, Segmentation. 1 Introduction In the image processing context, image segmentation is one of the main steps. Currently, most segmentation algorithms take into account color and texture of regions. Some of them also in- troduce geometrical criteria, like taking the shape of the object into account, to achieve a good segmentation.