摘要
论述了基于3种不变量的融合信息来识别缺损目标的方法.该方法采用Dempster-Shafer证据推理方法作为决策层的融合工具,将拐点、线矩、高阶神经网络的分类结果进行信息融合.分类实验证明,该方法可以有效地提高系统的识别精度.
This paper presents a method of recognizing occluded target with fused data,which comes from three kinds of invariances such as corner, moment and high order neural network. In this paper, Dempster Shafer Evidential reasoning is selected and used for data fusion at report level. The classification experiment shows that this method effectively improves the matching precision of the recognizing system.
出处
《武汉大学学报(自然科学版)》
CSCD
1998年第1期81-84,共4页
Journal of Wuhan University(Natural Science Edition)
基金
国防科工委预研基金
关键词
缺损目标识别
不变量
信息融合
模式识别
recognition of occluded target, invariance, data fusion, Dempster Shafer evidential reasoning