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.