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Image and Video Indexing using Networks of Operators

Abstract : This article presents a framework for the design of concept detection systems for image and video indexing. This framework integrates in a homogeneous way all the data and processing types. The semantic gap is crossed in a number of steps, each producing a small increase in the abstraction level of the handled data. All the data inside the semantic gap and on both sides included are seen as a homogeneous type called \em numcept and all the processing modules between the various numcepts are seen as a homogeneous type called \em operator. Concepts are extracted from the raw signal using networks of operators operating on numcepts. These networks can be represented as data-flow graphs and the introduced homogenizations allow fusing elements regardless of their nature. Low-level descriptors can be fused with intermediate of final concepts.
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Contributor : Marie-Christine Fauvet <>
Submitted on : Friday, February 28, 2014 - 4:00:56 PM
Last modification on : Friday, July 17, 2020 - 11:10:27 AM


  • HAL Id : hal-00953803, version 1



Stéphane Ayache, Georges Quénot. Image and Video Indexing using Networks of Operators. EURASIP Journal on Image and Video Processing, Springer, 2007. ⟨hal-00953803⟩



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