www.pudn.com > Digital_Image_Correlation_2010b.zip > RTCorrCode.m, change:2010-11-20,size:9282b


function [validx, validy, displx, disply]=RTCorrCode(grid_x,grid_y,straindir,Firstimagename) 
 
% Real time Correlation Code 
% 
% Written by Chris 
 
RTselection = menu(sprintf('End processing by end.txt or by last image?'),... 
    'Stop with end.txt','Stop with image check','Exit'); 
 
if RTselection==1 
end 
 
if RTselection==2 
end 
 
if RTselection==3 
    return 
end 
 
 
% Filename 
 
if exist('Firstimagename')==0 
    [Firstimagename ImageFolder]=uigetfile('*.tif','Open First Image'); 
    if Firstimagename~~[] 
        cd(ImageFolder); 
    end 
end 
 
if Firstimagename~~[] 
% Get the number of image name 
letters=isletter(Firstimagename); 
Pointposition=findstr(Firstimagename,'.'); 
Firstimagenamesize=size(Firstimagename); 
counter=Pointposition-1; 
counterpos=1; 
letterstest=0; 
while letterstest==0 
    letterstest=letters(counter); 
    if letterstest==1 
        break 
    end 
    Numberpos(counterpos)=counter; 
    counter=counter-1; 
    counterpos=counterpos+1; 
    if counter==0 
        break 
    end 
end 
 
Filename_first = Firstimagename(1:min(Numberpos)-1); 
Firstfilenumber=Firstimagename(min(Numberpos):max(Numberpos)); 
Lastname_first = Firstimagename(max(Numberpos)+1:Firstimagenamesize(1,2)); 
Firstfilenumbersize=size(Firstfilenumber); 
onemore=10^(Firstfilenumbersize(1,2)); 
filenamelist(1,:)=Firstimagename; 
h=figure; 
if exist('grid_x')==0 
    fpstest=1; 
    Filelist=[Firstimagename;Firstimagename]; 
    while fpstest==1 
        [grid_x,grid_y]=grid_generator(Firstimagename,ImageFolder); 
        [processingtime]=fpstestfunc(grid_x,grid_y,Filelist); 
        fpstest = menu(sprintf(['Processing the selected grid will allow ' , num2str(1/processingtime),' frames per second' ]),'Try again','Use the grid'); 
        if fpstest==1 
            clear grid_x; clear grid_y; 
        end 
    end 
end 
 
Firstfilenumber=str2num(Firstfilenumber); 
u=1+onemore+Firstfilenumber; 
ustr=num2str(u); 
filenamelist(2,:)=[Filename_first ustr(2:Firstfilenumbersize(1,2)+1) Lastname_first]; 
numberofimages=2; 
 
counter=1; 
 
input_points_x=grid_x; 
input_points_y=grid_y; 
base_points_x=grid_x; 
base_points_y=grid_y; 
base = uint8(mean(double(imread(filenamelist(1,:))),3));            % read in the base image ( which is always  image number one. You might want to change that to improve correlation results in case the light conditions are changing during the experiment 
numberofmarkers=max(size(grid_x))*min(size(grid_x)); 
validx(:,1)=reshape(grid_x,[],1); 
displx=zeros(numberofmarkers,1); 
validy(:,1)=reshape(grid_y,[],1); 
disply=zeros(numberofmarkers,1); 
tic 
 
while exist('end.txt','file') ==0; 
    pause(0.01); 
 
    if exist(filenamelist((counter+1),:),'file') ==2; 
        warning(['# Processed Images: ', num2str(numberofimages-1),'; # markers:',num2str(numberofmarkers), '; Processing Image: ',filenamelist(counter+1,:)])    % plot a title onto the image 
 
        input = mean(double(imread(filenamelist((counter+1),:))),3);       % read in the image which has to be correlated 
 
        input_points_for(:,1)=reshape(input_points_x,[],1);         % we reshape the input points to one row of values since this is the shape cpcorr will accept 
        input_points_for(:,2)=reshape(input_points_y,[],1); 
        base_points_for(:,1)=reshape(base_points_x,[],1); 
        base_points_for(:,2)=reshape(base_points_y,[],1); 
        input_correl(:,:)=cpcorr(round(input_points_for), round(base_points_for), input, base);           % here we go and give all the markers and images to process to cpcorr.m which ic a function provided by the matlab image processing toolbox 
        input_correl_x=input_correl(:,1);                                       % the results we get from cpcorr for the x-direction 
        input_correl_y=input_correl(:,2);                                       % the results we get from cpcorr for the y-direction 
 
        validx(:,counter+1)=input_correl_x;                                                     % lets save the data 
        savelinex=input_correl_x'; 
        dlmwrite('resultsimcorrx.txt', savelinex , 'delimiter', '\t', '-append');       % Here we save the result from each image; if you are desperately want to run this function with e.g. matlab 6.5 then you should comment this line out. If you do that the data will be saved at the end of the correlation step - good luck ;-) 
 
        validy(:,counter+1)=input_correl_y; 
        saveliney=input_correl_y'; 
        dlmwrite('resultsimcorry.txt', saveliney , 'delimiter', '\t', '-append'); 
 
        base_points_x=grid_x; 
        base_points_y=grid_y; 
        input_points_x=input_correl_x; 
        input_points_y=input_correl_y; 
 
        subplot(2,2,1) 
        imshow(filenamelist(counter+1,:))                     % update image 
        hold on 
        plot(grid_x,grid_y,'g+')                                % plot start position of raster 
        plot(input_correl_x,input_correl_y,'r+')        % plot actual postition of raster 
        hold off 
        drawnow 
 
        displx(:,counter+1)=validx(:,counter+1)-validx(:,1); 
        disply(:,counter+1)=validy(:,counter+1)-validy(:,1); 
 
        subplot(2,2,2) 
        xdata=validx(:,counter+1); 
        ydata=displx(:,counter+1); 
        if counter==1 
            x(1)=0 
            x(2)=0 
        end 
        [x,resnormx,residual,exitflagx,output]  = lsqcurvefit(@linearfit, [x(1) x(2)], xdata, ydata); 
        plot(xdata,ydata,'.'); 
        hold on; 
        ydatafit=x(1)*xdata+x(2); 
        plot(xdata,ydatafit,'r'); 
        hold off 
        xlabel('x-pos [pixel]') 
        ylabel('x-displ [pixel]') 
        title('x displ. versus x pos. in [pixel]') 
 
        slopex(counter,:)=[i x(1) x(2)]; 
 
        subplot(2,2,4) 
        xdata=validy(:,counter+1); 
        ydata=disply(:,counter+1); 
        if counter==1 
            y(1)=0 
            y(2)=0 
        end 
        [y,resnormx,residual,exitflagx,output]  = lsqcurvefit(@linearfit, [y(1) y(2)], xdata, ydata); 
        plot(xdata,ydata,'.g'); 
        hold on; 
        ydatafit=y(1)*xdata+y(2); 
        plot(xdata,ydatafit,'r'); 
        hold off 
        xlabel('y-pos [pixel]') 
        ylabel('y-displ [pixel]') 
        title('y displ. versus y pos. in [pixel]') 
 
        slopey(counter,:)=[i y(1) y(2)]; 
 
        subplot(2,2,3) 
        plot(slopex(:,2),'-b') 
        hold on 
        plot(slopey(:,2),'-g') 
        hold off 
        xlabel('Image # [ ]') 
        ylabel('x- and y-strain [ ]') 
        title('Strain in x and y direction versus Image #') 
 
        counter=counter+1; 
 
        u=1+u; 
        ustr=num2str(u); 
        filenamelist(counter+1,:)=[Filename_first ustr(2:Firstfilenumbersize(1,2)+1) Lastname_first]; 
        [numberofmarkers numberofimages]=size(validx); 
         
        if RTselection==2 
            if exist(filenamelist((counter+1),:),'file') ==0; 
                save validx.dat validx -ascii -tabs 
                save validy.dat validy -ascii -tabs 
                warning('Last image detected, RTCorrCode stopped') 
                return 
            end 
        end 
         
         
        subplot(2,2,1),title(['# Processed Images: ', num2str(numberofimages-1),'; fps: ', num2str((numberofimages-1)/toc),'; # markers:',num2str(numberofmarkers), '; Waiting for Image: ',filenamelist(counter+1,:)])    % plot a title onto the image 
 
    end 
end 
 
save validx.dat validx -ascii -tabs 
save validy.dat validy -ascii -tabs 
msgboxwicon=msgbox('end.txt file detected, RTCorrCode stopped','Processing stopped!') 
warning('end.txt file detected, RTCorrCode stopped') 
end 
 
%---------------------------------- 
% 
 
function [processingtime]=fpstestfunc(grid_x,grid_y,filenamelist) 
tic; 
 
input_points_x=grid_x; 
base_points_x=grid_x; 
 
input_points_y=grid_y; 
base_points_y=grid_y; 
 
% [row,col]=size(base_points_x);      % this will determine the number of rasterpoints we have to run through 
% [r,c]=size(filenamelist);                   % this will determine the number of images we have to loop through 
 
base = uint8(mean(double(imread(filenamelist(1,:))),3));            % read in the base image ( which is always  image number one. You might want to change that to improve correlation results in case the light conditions are changing during the experiment 
input = uint8(mean(double(imread(filenamelist(2,:))),3));       % read in the image which has to be correlated 
 
input_points_for(:,1)=reshape(input_points_x,[],1);         % we reshape the input points to one row of values since this is the shape cpcorr will accept 
input_points_for(:,2)=reshape(input_points_y,[],1); 
base_points_for(:,1)=reshape(base_points_x,[],1); 
base_points_for(:,2)=reshape(base_points_y,[],1); 
input_correl(:,:)=cpcorr(input_points_for, base_points_for, input, base);           % here we go and give all the markers and images to process to cpcorr.m which ic a function provided by the matlab image processing toolbox 
input_correl_x=input_correl(:,1);                                       % the results we get from cpcorr for the x-direction 
input_correl_y=input_correl(:,2);                                       % the results we get from cpcorr for the y-direction 
 
processingtime=toc;