中文摘要：

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。

英文摘要：

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.