Image Processing Reference
In-Depth Information
Chapter 10
Multi-Agent Methods: An Example of an
Architecture and its Application for the
Detection, Recognition and
Identification of Targets
The purpose of vision systems is to allow an understanding of the observed scene,
based on diverse data obtained from images. This scene is often characterized by a
non-homogenous, highly variable environment and any observation condition. Obvi-
ously, this general nature leads to very complex systems, including the need for scala-
bility, for the ability to provide intermediate results, the integration of uncertain knowl-
edge, or the possibility to adapt through the choice of strategies, operators and param-
eters.
The problem of vision that we have just introduced involves the detection, recog-
nition and identification (DRI) of targets such as military ground vehicles, boats and
aircraft. In this operational context, we have to be capable of making a decision as
quickly as possible, in order to assess the threat. A DRI system needs to constantly
search for the relevant information among a wealth of useless elements of informa-
tion. We propose a method based on multi-agent concepts to solve this problem. At
each instant, a population of agents works in parallel in the environment. Each agent
has descriptive and operational knowledge at its disposal to allow it to elaborate its
own strategy and to conduct processes. The set of results obtained is stored in a world
model shared by all the agents.
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