# Using 2D Topological Map Information in a Markovian Image Segmentation

Procedings of 11th Discrete Geometry for Computer Imagery, Volume 2886, pages 288-297 - November 2003

Topological map is a mathematical model of labeled image representation which contains both topological and geometrical information. In this work, we use this model to improve a Markovian segmentation algorithm. Image segmentation methods based on Markovian assumption consist in optimizing a Gibbs energy function. This energy function can be given by a sum of potentials which could be based on the shape or the size of a region, the number of adjacencies,... and can be computed by using topological map. In this work we propose the integration of a new potential: the global linearity of the boundaries, and show how this potential can be extracted from the topological map. Moreover, to decrease the complexity of our algorithm, we propose a local modification of the topological map in order to avoid the reconstruction of the entire structure.

## BibTex references

@InProceedings{DAB2003_1642,

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author | = {Damiand, G. and Alata, O. and Bihoreau, C.}, | |

title | = {Using 2D Topological Map Information in a Markovian Image Segmentation.}, | |

booktitle | = {Procedings of 11th Discrete Geometry for Computer Imagery}, | |

series | = {LNCS}, | |

volume | = {2886}, | |

pages | = {288-297}, | |

month | = {November}, | |

year | = {2003}, | |

address | = {Naples, Italy}, | |

url | = {http://springerlink.metapress.com/link.asp?id=9lgpgl9lbl3yg43n}, |