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Conference Papers Year : 2005

Weighted Adaptive Neighborhood Hypergraph Partitioning for Image Segmentation

Abstract

The aim of this paper is to present an improvement of a previously published algorithm. The proposed approach is performed in two steps. In the first step, we generate the Weighted Adaptive Neighborhood Hypergraph (WAINH) of the given gray-scale image. In the second step, we partition the WAINH using a multilevel hypergraph partitioning technique. To evaluate the algorithm performances, experiments were carried out on medical and natural images. The results show that the proposed segmentation approach is more accurate than the graph based segmentation algorithm using normalized cut criteria. Key words hypergraph, neighborhood hypergraph, hypergraph partitioning, image segmentation, edge detection and adaptive thresholding.
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Dates and versions

hal-01589732 , version 1 (19-09-2017)

Identifiers

  • HAL Id : hal-01589732 , version 1

Cite

Soufiane Rital, Serge Miguet, Hocine Cherifi. Weighted Adaptive Neighborhood Hypergraph Partitioning for Image Segmentation. 3rd International Conference on Advances in Pattern Recognition, Aug 2005, Bath, United Kingdom. pp.522-531. ⟨hal-01589732⟩
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