DocumentCode
538654
Title
A Novel Recognition Approach Based on Multi-agent
Author
Zhang Yong-Mei ; Ma Li ; Wei Qi ; Yang Yin-gang
Author_Institution
Sch. of Inf. Eng., North China Univ. of Technol., Beijing, China
Volume
1
fYear
2010
fDate
18-20 Dec. 2010
Firstpage
92
Lastpage
95
Abstract
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.
Keywords
geophysical image processing; image classification; infrared imaging; multi-agent systems; object recognition; remote sensing; sensor fusion; BDI model; SAR images; majority-decision algorithm; multi-agent object recognition model; multisensor remote sensing image recognition; near-infrared images; panchromatic images; property correlative analysis; remote sensing classification data; Framework; Multi-agent; Object recognition; Property related analysis; Remote sensing image;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Manufacturing and Automation (ICDMA), 2010 International Conference on
Conference_Location
ChangSha
Print_ISBN
978-0-7695-4286-7
Type
conf
DOI
10.1109/ICDMA.2010.20
Filename
5701107
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