0000000000403182

AUTHOR

Serge Miguet

0000-0001-7722-9899

showing 5 related works from this author

A segmentation algorithm for noisy images

2005

International audience; This paper presents a segmentation algorithm for gray-level images and addresses issues related to its performance on noisy images. It formulates an image segmentation problem as a partition of a weighted image neighborhood hypergraph. To overcome the computational difficulty of directly solving this problem, a multilevel hypergraph partitioning has been used. To evaluate the algorithm, we have studied how noise affects the performance of the algorithm. The alpha-stable noise is considered and its effects on the algorithm are studied. Key words : graph, hypergraph, neighborhood hypergraph, multilevel hypergraph partitioning, image segmentation and noise removal.

020203 distributed computingHypergraphMathematics::Combinatorics[ INFO ] Computer Science [cs]Computer sciencebusiness.industrySegmentation-based object categorizationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationImage processing02 engineering and technologyImage segmentation[INFO] Computer Science [cs]020202 computer hardware & architectureComputer Science::Computer Vision and Pattern Recognition0202 electrical engineering electronic engineering information engineeringGraph (abstract data type)SegmentationComputer vision[INFO]Computer Science [cs]Artificial intelligencebusinessAlgorithmMathematicsofComputing_DISCRETEMATHEMATICS
researchProduct

K-Way Hypergraph Partitioning And Color Image Segmentation

2006

International audience

[ INFO ] Computer Science [cs][INFO]Computer Science [cs][INFO] Computer Science [cs]ComputingMilieux_MISCELLANEOUS
researchProduct

Color Image Segmentation: The Hypergraph Framework

2006

International audience; Color Image Segmentation: The Hypergraph Framework

Physics::Popular PhysicsMathematics::Combinatorics[ INFO ] Computer Science [cs]Computer Science::Discrete MathematicsComputer Science::Computer Vision and Pattern RecognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO]Computer Science [cs][INFO] Computer Science [cs]ComputingMilieux_MISCELLANEOUSComputer Science::Computers and SocietyMathematicsofComputing_DISCRETEMATHEMATICS
researchProduct

Weighted Adaptive Neighborhood HypergraphPartitioning for Image Segmentation

2005

International audience; 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…

[ INFO ] Computer Science [cs]Computer Science::Computer Vision and Pattern RecognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO]Computer Science [cs][INFO] Computer Science [cs]MathematicsofComputing_DISCRETEMATHEMATICS
researchProduct

Neighborhood Hypergraph Partitioning for Image Segmentation

2005

International audience; The aim of this paper is to introduce a multilevel neighborhoodhypergraph partitioning for image segmentation. Our proposedapproach uses the image neighborhood hypergraph model introduced inour last works and the algorithm of multilevel hypergraphpartitioning introduced by George Karypis. To evaluate the algorithmperformance, experiments were carried out on a group of gray scaleimages. The results show that the proposed segmentation approachfind the region properly from images as compared to imagesegmentation algorithm using normalized cut criteria.Key words :Graph, Hypergraph, Neighborhood hypergraph, multilevel hypergraph partitioning, image segmentation, edge dete…

[ INFO ] Computer Science [cs]Computer Science::Computer Vision and Pattern RecognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO]Computer Science [cs][INFO] Computer Science [cs]MathematicsofComputing_DISCRETEMATHEMATICS
researchProduct