New Combination Rule in Evidence Theory Applied to Target Recognition of Sequential Images
一种新的证据组合规则应用于序列图像目标识别*

It presented a new combination rule of Dempster-Shafer evidence theory.The question of sequential image recognition was solved based on BP Neural Network(BPNN) and Dempster-Shafer evidence theory.Firstly,modified Hu invariant moments was used as the feature of the image,and BPNN was applied to identify the target.Secondly,basic belief assignment function was constructed through the output of the BPNN,and afterwards the new combination rule was used to finish the decision data fusion.Lastly,recognition of 3D airplane images was completed.The simulation results showed that this method is effective.