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Appendix III

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Appendix III

Averaging function:

[x1 y1]=size(image);

x2=x1/a ; y2=y1/b;

for ii=1:x2 for jj=1:y2 som=0;

for i1=1+a*(ii-1):a*ii for j1=1+b*(jj-1):b*jj

som=som + image(i1,j1);

end;

end;

averaged_photo(ii,jj)=som/(a*b) ; end;

end;

vector=reshape(averaged_photo,[],1);

%averaged_mat_imag=[averaged_mat_imag vector];

Images reading and preprocessing

clear clc

person_number = 50;

ph_per_person = 1;

alpha=5; % downsampling factor

a=2; b=2; % a and b are the averaging parameters

vertical_images=1; horizontal_images=1; % parameter for segmentation v*h images

verhor=vertical_images * horizontal_images ; save('verhor');

save('horizontal_images');

save('vertical_images');

cd('D:\Neural Networks\Program\fullprogram\Training 1');

III-1

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averaged_mat_imag=[];

for l=1:person_number for k=1:ph_per_person

aaa=strcat([num2str(k),' (',num2str(l),').jpg']) ; image=imread(aaa); % image=rgb2gray(image);

[x y]=size(image);

if mod(x,alpha)~=1 x=x-rem(x,alpha);

end

if mod(y,alpha)~=0 y=y-rem(y,alpha);

end x=x/alpha;

y=y/alpha;

for xs=1:x for ys=1:y

im(xs,ys)=image(2*xs,2*ys);

end;

end;

image=im;

averaging; % application of function [x y]=size(averaged_photo);

x11=floor(x/vertical_images);

y11=floor(y/horizontal_images);

for i=1:vertical_images %segmentation loop for j=1:horizontal_images %segmentation loop

i1=1 + x11*(i-1):x11*i;

j1=1+y11*(j-1):y11*j ;

imagenew = image(i1,j1); %display(i1) %display(j1)

mat_total{i,j,l,k}=imagenew; %imshow(imagenew) vector_image=reshape(imagenew,[],1);

vector_total{i,j,l,k}=vector_image;

end;

end;

end end

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cd ('D:\Neural Networks\Program\fullprogram\Training 1');

for i=1:vertical_images for j=1:horizontal_images for k=1:ph_per_person for l=1:person_number if l==1, input=[]; end

input=[input vector_total{i,j,l,k}];

end

if k==1, input1=[]; end

input1=[input1 input];

end

aa=strcat(['inputmat',num2str(i),num2str(j)]);

save(aa,'input1');

end end

images vectorazing

clc close

load('horizontal_images');

load('vertical_images');

neural_input=[];

for i=1:vertical_images for j=1:horizontal_images

aa=strcat(['inputmat',num2str(i),num2str(j),'.mat']);

load(aa);

neural_input=[neural_input input1];

end;

end;

save('neural_input');

target=[];

tar=eye(50);

load('verhor');

for i=1:1*verhor target=[target tar];

end;

save('target');

III-3

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