基于直方图的mass函数构造方法  

A Mass Function Construction Method Based on Histogram

作　　者：李文艺[1] 刘春[2] 李彪[1] 

机构地区：[1]宿州学院机械与电子工程学院,安徽宿州234000 [2]河南大学计算机与信息工程学院,河南开封475000

出　　处：《中山大学学报（自然科学版）》2014年第6期155-158,共4页Acta Scientiarum Naturalium Universitatis Sunyatseni

基　　金：国家杰出青年自然科学基金资助项目(61300035);宿州学院科研启动基金资助项目(2009yss08)

摘　　要：针对多特征融合的模式识别问题,给出了一种利用样本特征分布的直方图构造mass函数的方法。首先做出样本特征的直方图;在特征直方图的重叠区域,特征的不确定性较大;在特征直方图的非重叠区域,特征的确定性较大。然后,对于一个新的对象,若它的某一特征落入直方图的重叠区,由该特征构造的mass函数有较大的不确定性;若该特征落入直方图的非重叠区,则由该特征构成的mass函数确定性较大。把不同特征的mass函数进行融合得到最终的融合结果。对鸢尾属植物进行分类实验的正确率达到96.64%,实验结果表明了该方法的有效性。A method based on the histogram of the sample feature distribution is presented to construct the mass function,for the problem of pattern recognition using the multi-feature fusion.Firstly,the sam-ple feature distribution is established.In the overlapping area of the histogram,the feature is uncertain;while in the no-overlapping area of the histogram the feature is determinate.Then,for a new object,if one of its features falls into the overlapping region of the histogram,the mass function constructed by this feature has a larger uncertainty;if the feature falls into non-overlapping region of the histogram,the mass function constructed by this feature has a greater certainty.The mass functions of different features are fused to get the fusion result.The correct ratio of the iris-plant classify experiment is 96.64%,and the result shows that this method is feasible.

关 键 词：证据理论 基本概率赋值函数 直方图 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]