6533b855fe1ef96bd12b10a1
RESEARCH PRODUCT
Hypergraph imaging: an overview
Alain BrettoHocine CherifiDriss Aboutajdinesubject
HypergraphTheoretical computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingImage segmentationEdge detectionScale spaceArtificial IntelligenceComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingCombinatorial optimizationComputer Vision and Pattern RecognitionRepresentation (mathematics)SoftwareMathematicsofComputing_DISCRETEMATHEMATICSFeature detection (computer vision)Mathematicsdescription
Hypergraph theory as originally developed by Berge (Hypergraphe, Dunod, Paris, 1987) is a theory of finite combinatorial sets, modeling lot of problems of operational research and combinatorial optimization. This framework turns out to be very interesting for many other applications, in particular for computer vision. In this paper, we are going to survey the relationship between combinatorial sets and image processing. More precisely, we propose an overview of different applications from image hypergraph models to image analysis. It mainly focuses on the combinatorial representation of an image and shows the effectiveness of this approach to low level image processing; in particular to segmentation, edge detection and noise cancellation.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2002-03-01 | Pattern Recognition |