Since the agent is autonomous, cooperative and distributed, and it is based on the BDI model of the agent, the paper describes the process of object recognition on the basis of multi-sensor remote sensing images using multi-agent system, proposes a multi-agent object recognition model(MAORM) which combines concurrency research results and the specific characteristics of multi-sensor remote sensing image recognition. In order to improve recognition probability, the task of multi-source remote sensing image recognition for near-infrared, panchromatic and SAR images can be accomplished by the model, and the features that are sensitive to remote sensing classification data are selected through property correlative analysis. Compared with the current object recognition methods, the proposed framework is more close to the human vision. A majority-decision algorithm based on multi-agent is presented. The paper proposes a new approach in decision fusion, the method uses less data than other fusion, and improves the reliability. Experiment results show that the system can effectively identify the bridges, wharfs, ships and so on. Compared with a single remote sensing image, the system can effectively recognize targets with higher recognition accuracy and lower error recognition rate, and achieve the distributed object processing.
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