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ICAPR
2005
Springer

Weighted Adaptive Neighborhood Hypergraph Partitioning for Image Segmentation

10 years 3 months ago
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.
Soufiane Rital, Hocine Cherifi, Serge Miguet
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where ICAPR
Authors Soufiane Rital, Hocine Cherifi, Serge Miguet
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