Attributed skeleton graphs using mathematical morphology

The aim of the work described is to use the potential strength of the skeleton of discrete objects in computer vision and pattern recognition where features of objects are needed for classification. Algorithms are introduced for detecting skeleton characteristic points (end points, junction points and curve points) and creating an attributed graph, that can then be used as an input to graph matching algorithms, based on a morphological approach.

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