please help me about eigenfaces error matlab?

% Face recognition by Santiago Serrano
clear all close all clc % number of images on your training set. InputImage1=imread('1.jpg'); InputImage1=rgb2gray(InputImage1);
M=1;
% Chosen std and mean. % It can be any number that it is close to the std and mean of most of the images. um=100; ustd=80;
% read and show image S=[]; % img matrix
figure(1); for i=1:M img = InputImage1; %img = rgb2gray(img); img = imresize (img, [10 10],'bilinear'); %subplot (ceil(sqrt(M)),ceil(sqrt(M)),i); imshow(img) if i==3 title('Training set','fontsize',18) end drawnow; [irow icol]=size(img); % get the number of rows (N1) and columns (N2) temp=reshape(img',irow*icol,1); % creates a (N1*N2)x1 vector S=[S temp]; % S is a N1*N2xM matrix after finishing the sequence end
% Here we change the mean and std of all images. We normalize all images. % This is done to reduce the error due to lighting conditions and background. for i=1:size(S,2) temp = double(S(:,i)); m = mean(temp); st = std(temp); S(:,i)=(temp-m)*ustd/st+um; end
% show normalized images %figure(2); for i=1:M str=strcat(int2str(i),'.jpg'); img=reshape(S(:,i),icol,irow); img=img'; %eval('imwrite(img,str)'); %subplot(ceil(sqrt(M)),ceil(sqrt(M)),i) imshow(img) drawnow; if i==3 title('Normalized Training Set','fontsize',18) end end
% mean image m = mean(S,2); % obtains the mean of each row instead of each column tmimg = uint8(m); % converts to unsigned 8-bit integer. Values range from 0 to 255 img = reshape(tmimg,icol,irow); % takes the N1*N2x1 vector and creates a N1xN2 matrix img = img'; %figure(3); imshow(img); %title('Mean Image','fontsize',18)
% Change image for manipulation dbx=[]; % A matrix for i=1:M temp=double(S(:,i)); dbx=[dbx temp]; end
%Covariance matrix C=A'A, L=AA' A=dbx'; L=A*A'; % vv are the eigenvector for L % dd are the eigenvalue for both L=dbx'*dbx and C=dbx*dbx'; [vv dd]=eig(L); % Sort and eliminate those whose eigenvalue is zero v=[]; d=[]; for i=1:size(vv,2) if(dd(i,i)>1e-4) v=[v vv(:,i)]; d=[d dd(i,i)]; end end
%sort, will return an ascending sequence [B index]=sort(d); ind=zeros(size(index)); dtemp=zeros(size(index)); vtemp=zeros(size(v)); len=length(index); for i=1:len dtemp(i)=B(len+1-i); ind(i)=len+1-index(i); vtemp(:,ind(i))=v(:,i); end d=dtemp; v=vtemp;
%Normalization of eigenvectors for i=1:size(v,2) %access each column kk=v(:,i); temp=sqrt(sum(kk.^2)); v(:,i)=v(:,i)./temp; end
%Eigenvectors of C matrix u2=[]; for i=1:size(v,2) temp=sqrt(d(i)); u2=[u2 (dbx*v(:,i))./temp]; end
%Normalization of eigenvectors for i=1:size(u2,2) kk=u2(:,i); temp=sqrt(sum(kk.^2)); u2(:,i)=u2(:,i)./temp; end
% show eigenfaces %figure(4); for i=1:size(u2,2) img=reshape(u2(:,i),icol,irow); img=img'; img=histeq(img,255); subplot(ceil(sqrt(M)),ceil(sqrt(M)),i) imshow(img) drawnow; if i==3 title('Eigenfaces','fontsize',18) end end
% Find the weight of each face in the training set omega = []; for h=1:size(dbx,2) WW=[]; for i=1:size(u2,2) t = u2(:,i)'; WeightOfImage = dot(t,dbx(:,h)'); WW = [WW; WeightOfImage]; end
omega = [omega WW]; end
% Acquire new image % Note: the input image must have a bmp or jpg extension. % It should have the same size as the ones in your training set. % It should be placed on your desktop InputImage = input('Please enter the name of the image and its extension \n','s'); InputImage = imread(strcat('E:\pindahan\SKRIPSI JADI1\',InputImage)); %figure(5) %subplot(1,2,1)
imshow(InputImage); colormap('gray'); title('Input image','fontsize',18) InImage=reshape(InputImage',irow*icol,1); temp=InImage; me=mean(temp); st=std(temp); temp=(temp-me)*ustd/st+um; NormImage = temp; Difference = temp-m;
p = []; aa=size(u,2); for i = 1:aa pare = dot(NormImage,u(:,i)); p = [p; pare]; end
ReshapedImage = m + u(:,1:aa)*p; %m is the mean image, u is the eigenvector ReshapedImage = reshape(ReshapedImage,icol,irow); ReshapedImage = ReshapedImage'; %show the reconstructed image. %subplot(1,2,2) imagesc(ReshapedImage); colormap('gray'); title('Reconstructed image','fontsize',18)
InImWeight = []; for i=1:size(u,2) t = u(:,i)'; WeightOfInputImage = dot(t,Difference'); InImWeight = [InImWeight; WeightOfInputImage]; end
ll = 1:M; %figure(68) %subplot(1,2,1) stem(ll,InImWeight) title('Weight of Input Face','fontsize',14)
% Find Euclidean distance e=[]; for i=1:size(omega,2) q = omega(:,i); DiffWeight = InImWeight-q; mag = norm(DiffWeight); e = [e mag]; end
kk = 1:size(e,2); subplot(1,2,2) stem(kk,e) title('Eucledian distance of input image','fontsize',14)
MaximumValue=max(e); % maximum eucledian distance MinimumValue=min(e); % minimum eucledian distance

please help me. i dont understand with this program . error in ???

**Error using ==> ctranspose Transpose on ND array is not defined.

Error in ==> eigenface at 171* InImage=reshape(InputImage',irow*icol,1);*

Answer 1

[Image Analyst]

Sounds like you're trying to transpose a color image, InputImage, and it does not know how to transpose a 3D matrix. Maybe you need to comvert it to grayscale with

grayImage = rgb2gray(InputImage);

or extract just one of the color channels

grayImage = InputImage(:,:,2); % Extract green channel.