Abstract
A method allowing to integrate syntactic and semantic approaches in an automatic segmentation process is described. This integration is possible thanks to the formalism of graphs. The proposed method checks the relevancy of merging criteria used in an adaptive pyramid by matching the obtained segmentation with a semantic graph describing the objects that we look for. This matching is performed by checking the arc-consistency with bilevel constraints of the chosen semantic graph. The validity of this approach is experimented on synthetic and real images.
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© 2005 Springer-Verlag Berlin Heidelberg
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Deruyver, A., Hodé, Y., Leammer, E., Jolion, JM. (2005). Adaptive Pyramid and Semantic Graph: Knowledge Driven Segmentation. In: Brun, L., Vento, M. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2005. Lecture Notes in Computer Science, vol 3434. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31988-7_20
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DOI: https://doi.org/10.1007/978-3-540-31988-7_20
Publisher Name: Springer, Berlin, Heidelberg
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