The Star-Topology: a topology for image analysis

Abstract : Our previous works in image analysis dealing with image representations by means of adjacency or boundary graphs, led us to the need for a coherent representation model. In fact, classical approaches to this problem seem to be unsuffcient or even uncoherent; for example they are unclear with the well-known connectivity paradox or with the border description of regions. Diierent works like those of Kovalevsky, Herman and Malandain pointed out the advantages of cellular complex based topologies [Kovalevsky89, Herman90, Malandain93]. But no one of them suggested a formalism that can be applied to any type of image. In this work we propose a topological representation for any type of image, colour or grey-level of whatever dimension. It is based on convex complexes, and looks closely at the elements realizing the connectivity within complexes and later within regions. Futhermore it remains coherent with pixel and voxel only based representations. An important feature is still maintaining a direct correspondance with the classical IR n topology. Finally, we suggest a characterization of regions, their borders and boundaries which is useful as a basic tool for segmentation.
Document type :
Conference papers
Complete list of metadatas

Cited literature [9 references]  Display  Hide  Download

https://hal-lirmm.ccsd.cnrs.fr/lirmm-01168307
Contributor : Christophe Fiorio <>
Submitted on : Thursday, June 25, 2015 - 4:01:31 PM
Last modification on : Thursday, September 5, 2019 - 11:42:10 AM
Long-term archiving on: Friday, October 9, 2015 - 5:36:28 PM

File

1995-DGCI.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : lirmm-01168307, version 1

Collections

Citation

Ehoud Ahronovitz, Jean-Pierre Aubert, Christophe Fiorio. The Star-Topology: a topology for image analysis. DGCI: Discrete Geometry for Computer Imagery, 1995, Clermont-Ferrand, France. ⟨lirmm-01168307⟩

Share

Metrics

Record views

388

Files downloads

454