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Proceedings Paper

Inference for data fusion
Author(s): Lei-Jian Liu; Y. G. Gu; Jingyu Yang
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Paper Abstract

Data fusion has been widely used in various fields of automation. This paper describes a multisensor integration system: range and intensity image processing system, which can be used for object recognition and classification. In the data fusion processing, a new method called generalized evidence inference method is used by the system. The method presented here unifies both Bayesian theory and Dempster-Shafer's evidential reasoning (DSER) for the combination of information from diversified sources, and overcomes the disadvantages of both approaches. At the same time, we adopt these three approaches: the Bayesian theory, the DSER, and the unified approach to fuse the reports in the system for object recognition and classification, the results are compared and analyzed.

Paper Details

Date Published: 16 December 1992
PDF: 8 pages
Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); doi: 10.1117/12.130872
Show Author Affiliations
Lei-Jian Liu, East China Institute of Technology (United States)
Y. G. Gu, East China Institute of Technology (China)
Jingyu Yang, East China Institute of Technology (China)


Published in SPIE Proceedings Vol. 1766:
Neural and Stochastic Methods in Image and Signal Processing
Su-Shing Chen, Editor(s)

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