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Coarse-to-Fine Object Recognition Using Shock Graphsctly segmented. In this paper, we present a framework for shock graph-based object recognition in less contrived scenes. The approach consists of two steps, beginning with the construction of a region adjacency graph pyramid. For a given region, we traverse this scale-space, using a model shock grap

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https://doi.org/10.1007/978-3-030-93383-8 a lot of problems of operational research and combinatorial optimization. Hypergraphs are now used in many domains such as chemistry, engineering and image processing. We present an overview of a hypergraph-based picture representation giving much application in picture manipulation, analysis and r

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https://doi.org/10.1007/978-3-031-63091-0sequently used in image processing and understanding. A digital image is processed to extract edge pixel chains and a constrained Delaunay triangulation of the edge contour set is performed to yield triangles that cover the pixelated image without crossing edge contours. Each triangle is attributed

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https://doi.org/10.1007/978-3-662-08797-8ved: a graph representing the contents of a document image at some level of interpretation, a set of graph transformation rules (graph productions), and a mechanism for controlling the application of the graph productions. We review existing document analysis systems that use graph transformation, a

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Modelling Future Telecommunications Systemsgnition systems. We present here a “generic” formalism for graphical knowledge, allowing various modellings for a given graphical shape. We use a modelling library based on this formalism for the management of our graphical knowledge. The use of this library allows to request graphical knowledge dat

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Modelling Hot Deformation of Steels (intussusception). Graph theory is a branch of discrete mathematics that is excellently suited to model vascular networks and to analyze their properties (invariants). A random graph process model can simulate the development of a vascular network that has been modeled using graph theory. The renal

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https://doi.org/10.1007/978-94-007-7648-7n important task in network analysis problem in routine and bioinformatics. In this paper we show how the problem of graph seriation can be solved using semi-definite programming (SDP). This is a convex optimisation procedure that has recently found widespread use in computer vision. The main contri