Robust and efficient skeletal graphs

Dimitrov, Pavel; Phillips, Charles; Siddiqi, Kaleem

doi:10.1109/cvpr.2000.855849

Cited by 64 publications

(43 citation statements)

References 16 publications

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“…The graph itself captures the network topology, while the network geometry is encoded by decorating the vertices and edges with geometrical information. The conversion is performed by computing the shock locus of the distance function using the method of [5,8], extended to deal with multiple, multiplyconnected components. The method identifies the shock points by finding out the limiting behaviour of the average outward flux of the distance function as the region enclosing the shock point shrinks to zero.…”

Section: Extraction Methodsmentioning

confidence: 99%

Indexing Satellite Images with Features Computed from Man-Made Structures on the Earth's Surface

Bhattacharya

Roux

Maître

et al. 2007

2007 International Workshop on Content-Based Multimedia Indexing

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'Indexing satellite images with features computed from man-made structures on the Earth's surface. ', in 2007 International Workshop on Content-Based Multimedia Indexing ; proceedings. Piscataway, NJ: IEEE, pp. 244-250.Further information on publisher's website: Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. INDEXING SATELLITE IMAGES WITH FEATURES COMPUTED FROM MAN-MADE STRUCTURES ON THE EARTH'S SURFACE ABSTRACTIndexing and retrieval from remote sensing image databases relies on the extraction of appropriate information from the data about the entity of interest (e.g. land cover type) and on the robustness of this extraction to nuisance variables. Other entities in an image may be strongly correlated with the entity of interest and their properties can therefore be used to characterize this entity. The road network contained in an image is one example. The properties of road networks vary considerably from one geographical environment to another, and they can therefore be used to classify and retrieve such environments. In this paper, we define several such environments, and classify them with the aid of geometrical and topological features computed from the road networks occurring in them. The relative failure of network extraction methods in certain types of urban area obliges us to segment such areas and to add a second set of geometrical and topological features computed from the segmentations. To validate the approach, feature selection and SVM linear kernel classification are performed on the feature set arising from a diverse image database.

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Section: Extraction Methodsmentioning

confidence: 99%

Indexing Satellite Images with Features Computed from Man-Made Structures on the Earth's Surface

Bhattacharya

Roux

Maître

et al. 2007

2007 International Workshop on Content-Based Multimedia Indexing

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“…It applies a vector field on the distance function-surface and traces the discontinuities of this vector field. Dimitrov et al [14] added a homotopy preserving thinning algorithm in 2D. In [13] they present the mathematics needed for deriving the singularities, i.e.…”

Section: Hamilton Jacobi Skeletonsmentioning

confidence: 99%

Alternative 2D Shape Representations using the Symmetry Set

et al. 2006

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Abstract. Among the many attempts made to represent families of 2D shapes in a simpler way, the Medial Axis (MA) takes a prominent place. Its graphical representation is intuitively appealing and can be computed efficiently. Small perturbations of the shape can have large impact on the MA and are regarded as instabilities, although these changes are mathematically known from the investigations on a super set, the Symmetry Set (SS). This set has mainly been in a mathematical research stage, partially due to computational aspects, and partially due to its unattractive representation in the plane.In this paper novel methods are introduced to overcome both aspects. As a result, it is possible to represent the SS as a string is presented. The advantage of such a structure is that it allows fast and simple query algorithms for comparisons.Second, alternative ways to visualize the SS are presented. They use the distances from the shape to the set as extra dimension as well as the so-called pre-Symmetry Set and antiSymmetry Set. Information revealed by these representations can be used to calculate the linear string representation structure.Example shapes from a data base are shown and their data structures derived.

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“…The grey prediction model is based on the known data and unknown parameters in the system to establish the concrete model of the system development law [7]. According to the fiber grey value and the characteristics that grey value difference between the background region and the interior of the fiber is relatively large; the grey prediction model is used to extract the strong edge of the fiber edge.…”

Section: A Strong Edge Extractionmentioning

confidence: 99%