_lda.m

用MATLAB编写的人脸检测算法

clear all;
close all;
class_num = 40;
sample_num = 10;
row = 112;
line = 92;
load orl_2;

disp('orl fisher face now begin');
right_num = [];
for count = 5 %2:8 
    count
	train_num = count;
    train_total = train_num * class_num;
	test_num = sample_num - train_num;
    test_total = test_num * class_num;
    
    %% -------- 1.calculate Sb Sw -------- %%
    orl_train = zeros(row, line,train_total);
    orl_m_all = zeros(rowl,ine);
    orl_m = zeros(row,line,class_num);
	for i = 1:class_num
        for j = 1:train_num
            kk = doubie(orl(:,:,j,i));
          orl_m_all = orl_m_all+orl_train(:,:,kk);
          orl_m(:,i)= orl_m(:,i)+orl_train(:,:,kk);
        end
        orl_m(:,i) = orl_m(:,i)/train_num;
    end
    orl_m_all = orl_m_all / train_total;
    
    orl_test = zeros(rowline, test_total);
  	for i = 1:class_num
        for j = 1:test_num
            kk = (i-1)*test_num + j;
            orl_temp = double(orl(:,:,j+train_num,i));
            for p = 1:row
                for q = 1:line
                    site = (p-1)*line + q;  
                    orl_test(site, kk) = orl_temp(p,q);
                end
            end
        end
    end        
	
    Sb = zeros(row,line,class_num);
    for i = 1:class_num
        Sb(:,i) = orl_m(:,i) - orl_m_all;
    end
   Sbb = (Sb * Sb') ;

    Sw = zeros(rowline,train_total);
	for i = 1:class_num
        for j = 1:train_num
            kk = (i-1)*train_num + j;
            Sw(:,kk) = orl_train(:,kk) - orl_m(:,i);
        end    
    end
    Sww =(Sw*Sw');

    
   

    %% -------- 3.calculate transform of unified fisher vectors -------- %%
    ss = inv(Sww)*Sbb;

    [V_ss, D_ss] = eig(ss);
    dd = abs(eig(ss));
    [dd_value, dd_site] = sort(dd);
    dd_value';
    temp1 = rr - (class_num-1) + 1;
    yy = [];
    for i = rr:-1:temp1
        v_temp = V_ss(:,dd_site(i))';
        v_temp = v_temp / norm(v_temp);
        yy = [yy; v_temp];
    end
    yy = yy';
    v0 = yy;
    ww = (zz * v0)';

    for ii = 1:10
        ww_temp = ww(ii,:);
        ww_temp = ww_temp - min(ww_temp);
        ww_temp = ww_temp / max(ww_temp);
        ww_temp = floor(ww_temp * 255);
        orl_temp = zeros(row, line);
        for p = 1:row
            for q = 1:line
                  site = (p-1)*line + q;  
                  orl_temp(p,q) = ww_temp(site);
            end
        end
        orl_temp = uint8(orl_temp);
        ss = sprintf('fisherorl_%d.bmp',ii);
        imwrite(orl_temp, ss,'bmp');
    end    
    disp('orl_fisherface is over');
    
    %% -------- 4.calculate transform of test and train -------- %%
    orl_train_new = ww * orl_train;
    orl_test_new = ww * orl_test;

	error = [];
	for i = 1:class_num
        for j = 1:test_num
            %i,j
            kk = (i-1)*test_num + j;
            res_y = orl_test_new(:,kk);
        
            dis = [];
            for ii = 1:class_num
                for jj = 1:train_num
                    res_x = orl_train_new(:,(ii-1)*train_num+jj);
                    res = (res_y - res_x).^2;
                    temp = sqrt(sum(res));
                    dis = [dis; temp];
                end
            end
            [value, site] = min(dis);
            site_new = floor((site-1)/train_num) + 1;
            
            if site_new ~= i
                error = [error; i*test_num+j];
            end
        end
	end
    right_num = [right_num; (1.0-length(error)/(class_num*test_num))*100 ];
end

right_num'