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Recognition 的代码
recognition.m
%
% 文本文件sDataFile必须为以下格式：
% Database D:\kk.h\study\人脸库\ORL\92x112\
% TrainSet 1
% TestSet 2,3,4,5,6,7,8,9,10
%
% Database D:\kk.h\study\人脸库\ORL\92x112\
% TrainSet 1,2,3
% TestSet 4,5,6,7,8,
recognition.m
%
% 文本文件sDataFile必须为以下格式：
% Database D:\kk.h\study\人脸库\ORL\92x112\
% TrainSet 1
% TestSet 2,3,4,5,6,7,8,9,10
%
% Database D:\kk.h\study\人脸库\ORL\92x112\
% TrainSet 1,2,3
% TestSet 4,5,6,7,8,
recognition.m
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
recognition.m
function OutputName = Recognition(TestImage, m, A, Eigenfaces)
ProjectedImages = [];
Train_Number = size(Eigenfaces,2);
for i = 1 : Train_Number
temp = Eigenfaces'*A(:,i); % Projection of ce
recognition.m
function OutputName = Recognition(TestImage, m, A, Eigenfaces)
% Recognizing step....
%
% Description: This function compares two faces by projecting the images into facespace and
% measuring the
recognition.m
function [Numeral]=Recognition(StrokeTop,StrokeLeft,StrokeRight,StrokeBottom,Comp)
% 采用四边的轮廓结构特征和笔划统计（仅针对 0 和 8）识别残缺数字
% Comp 是用于识别 0和8 的底部补充信息
StrT='T';
StrL='T';
StrR='T';
StrB='T';
RStr='T';
recognition.m
function OutputName = Recognition(TestImage, m, A, Eigenfaces)
% Recognizing step....
%
% Description: This function compares two faces by projecting the images into facespace and
% measuring the
recognition.m
function [Numeral]=Recognition(StrokeTop,StrokeLeft,StrokeRight,StrokeBottom,Comp)
% 采用四边的轮廓结构特征和笔划统计（仅针对 0 和 8）识别残缺数字
% Comp 是用于识别 0和8 的底部补充信息
StrT='T';
StrL='T';
StrR='T';
StrB='T';
RStr='T';
recognition.m
function [Numeral]=Recognition(StrokeTop,StrokeLeft,StrokeRight,StrokeBottom,Comp)
% 采用四边的轮廓结构特征和笔划统计（仅针对 0 和 8）识别残缺数字
% Comp 是用于识别 0和8 的底部补充信息
StrT='T';
StrL='T';
StrR='T';
StrB='T';
RStr='T';