%0 Journal Article
%T New Combination Rule in Evidence Theory Applied to Target Recognition of Sequential Images<br>一种新的证据组合规则应用于序列图像目标识别*
%A YANG Yang
%A CHENG Yong-mei
%A PAN Quan
%A ZHANG Hong-cai
%A MIAO Zhuang
%A <br>杨阳
%A 程咏梅
%A 潘泉
%A 张洪才
%A 苗壮
%J 计算机应用研究
%D 2007
%I 
%X 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.
%K target recognition
%K D-S evidence reasoning
%K sequential image
%K BP neural network
%K combination rules<br>目标识别
%K D-S证据理论
%K 序列图像
%K 反向传播神经网络
%K 组合规则
%K 证据推理
%K 组合规则
%K 应用
%K 序列图像
%K 图像目标识别
%K Images
%K Sequential
%K Target
%K Recognition
%K Evidence
%K Theory
%K 融合方法
%K 仿真结果
%K 飞机
%K 三维
%K 决策级数据融合
%K 置信指派函数
%K 构造
%K 融合处理
%K 时间域
%K 思想
%K 利用
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=EF4AD2E7BFCF0B3054E0BFD1E4F60AAB&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=E158A972A605785F&sid=C5F8B8CB20F1B3D8&eid=9D453329DCCABB94&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=9