Integrated active contours for texture segmentation

Chen Sagiv*, Nir A. Sochen, Yehoshua Y. Zeevi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

172 Scopus citations

Abstract

We address the issue of textured image segmentation in the context of the Gabor feature space of images. Gabor filters tuned to a set of orientations, scales and frequencies are applied to the images to create the Gabor feature space. A two-dimensional Riemannian manifold of local features is extracted via the Beltrami framework. The metric of this surface provides a good indicator of texture changes and is used, therefore, in a Beltrami-based diffusion mechanism and in a geodesic active contours algorithm for texture segmentation. The performance of the proposed algorithm is compared with that of the edgeless active contours algorithm applied for texture segmentation. Moreover, an integrated approach, extending the geodesic and edgeless active contours approaches to texture segmentation, is presented. We show that combining boundary and region information yields more robust and accurate texture segmentation results.

Original languageEnglish
Pages (from-to)1633-1646
Number of pages14
JournalIEEE Transactions on Image Processing
Volume15
Issue number6
DOIs
StatePublished - Jun 2006

Funding

FundersFunder number
Israel Academy of Science
Israeli Ministry of Science
Ollendorf Minerva Center
Multidisciplinary University Research InitiativeN000M-01-1-0625
Tel Aviv University
Technion-Israel Institute of Technology

    Keywords

    • Active contours without edges
    • Anisotropic diffusion
    • Beltrami framework
    • Gabor analysis
    • Geodesic active contours
    • Image manifolds
    • Texture segmentation

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