Inference for data fusion

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.