recognition.m

来自「使用Fisher线性鉴别分析（FLDA）方法在ORL人脸数据库上进行人脸识别试验」· M 代码 · 共 30 行

function Accuracy=Recognition(TrainFeature,TestFeature);
%使用最近邻法进行识别
%输入TrainFeature为训练样本特征集；Test为Feature测试样本特征集
%返回值：Accuracy为正确识别率


[dim,TN_per,C]=size(TrainFeature);
SN_per=size(TestFeature,2);

wrong=0;
for ce=1:C
    for te=1:SN_per
        min_distance=1e+106;
        for ct=1:C
            for tt=1:TN_per
                V=TestFeature(:,te,ce)-TrainFeature(:,tt,ct);
                distance=norm(V,2);
                if distance<min_distance
                    min_distance=distance;
                    cy=ct;
                end
            end
        end
        if cy~=ce
            wrong=wrong+1;
        end
    end
end
           
Accuracy=(1-wrong./(SN_per*C))*100;