Dempster-Shafer reasoning with application multisensor object recognition system

Author

Zhang, Xin-Man ; Han, Jiu-qiang ; Xu, Xue-Bin

Author_Institution

Sch. of Electron. & Inf. Eng., Xi´´an Jiaotong Univ., China

Volume

2

fYear

2004

fDate

26-29 Aug. 2004

Firstpage

975

Abstract

Firstly by analyzing comprehensively the different sensor acquisitions based on normal distribution, a mathematical model is established to attain the basic probability assignments. Following this a multisensor data fusion method-based Dempster-Shafer reasoning is proposed to resolve object recognition problems. Offered by multilevel accumulation of assignments recursively the fusion estimates based on global information is obtained to testify the recognition performance. It is optimal than that of a single sensor with an average decline 74 percent of uncertainty value in a case study of pyrites recognition system, thereby demonstrating the effectiveness and correctness of this approach.

Keywords

inference mechanisms; normal distribution; object recognition; sensor fusion; Dempster-Shafer reasoning; multisensor data fusion method; multisensor object recognition system; normal distribution; pyrites recognition system; sensor acquisitions; Continuing education; Electronic mail; Information analysis; Mathematical model; Object detection; Object recognition; Recursive estimation; Sensor systems; Testing; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on

Print_ISBN

0-7803-8403-2

Type

conf

DOI

10.1109/ICMLC.2004.1382328

Filename

1382328