Mars: a multiple agent image interpretation system

Author

Hongbiao, Zhao ; Lizhu, Zhou

Author_Institution

Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China

Volume

2

fYear

1997

fDate

28-31 Oct 1997

Firstpage

1052

Abstract

Mars is both a spectrum and a structured knowledge based multiple agent interpretation system for remote sensing images. It represents the required knowledge in various schema closest to its original form by a blackboard structure. Mars uses a working-frame to hold a description of the traits and hypotheses addressed by agents. It supports a set of standard operations used to manipulate the data in the blackboard by all agents to integrate heterogeneous knowledge representation. By using a combined method of dynamic trait extraction and level conflict resolution respectively, Mars handles conflicts within and among agents. This paper discusses the design and implementation of Mars, including its architecture, mechanisms and implementation environment, and future work

Keywords

blackboard architecture; brightness; cooperative systems; explanation; feature extraction; image colour analysis; image texture; remote sensing; software agents; Mars; blackboard structure; brightness; color; dynamic trait extraction; earth resource satellites; extracting features; heterogeneous knowledge representation; hypotheses; image traits; level conflict resolution; light stimulation; multiple agent image interpretation system; remote sensing images; shadow; shape; size; texture; traits; Brightness; Communication system control; Computer science; Data mining; Feature extraction; Image analysis; Knowledge representation; Mars; Pixel; Remote sensing; Satellites;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-4253-4

Type

conf

DOI

10.1109/ICIPS.1997.669138

Filename

669138