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N. Simou Th. Athanasiadis G. Stoilos S. Kollias 《Signal, Image and Video Processing》2008,2(4):321-335
The effective management and exploitation of multimedia documents requires the extraction of the underlying semantics. Multimedia
analysis algorithms can produce fairly rich, though imprecise information about a multimedia document which most of the times
remains unexploited. In this paper we propose a methodology for semantic indexing and retrieval of images, based on techniques
of image segmentation and classification combined with fuzzy reasoning. In the proposed knowledge-assisted analysis architecture
a segmentation algorithm firstly generates a set of over-segmented regions. After that, a region classification process is
employed to assign semantic labels using a confidence degree and simultaneously merge regions based on their semantic similarity.
This information comprises the assertional component of a fuzzy knowledge base which is used for the refinement of mistakenly
classified regions and also for the extraction of rich implicit knowledge used for global image classification. This knowledge
about images is stored in a semantic repository permitting image retrieval and ranking.
This research was supported by the European Commission under contract FP6-027026 K-SPACE. 相似文献
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