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.

• Type: Conference
• Year: 2005
• Where: ICAPR
• Authors: Soufiane Rital, Hocine Cherifi, Serge Miguet
• Keywords: Adaptive Neighborhood Hypergraph, Hypergraph Partitioning Technique, ICAPR 2005, Neighborhood Hypergraph