Code error of shade matching (Image processing).

This is my matlab code for shade matching. Actually I copy it from this website also. But the code is not running in my laptop which is matlab version R2014A. Would you please tell me how to fix the code error? Is there any additional config that I need to do before run the code? here I attached my m.file also.

   workspace;
  fontSize = 20;
  fullImageFileName = 'C:\Users\user\Desktop\FYP pic\Single teeth.JPG';
  % Read in image into an array.
    [rgbImage, storedColorMap] = imread(fullImageFileName); 
    [rows, columns, numberOfColorBands] = size(rgbImage); 
    % If it's monochrome (indexed), convert it to color. 
    % Check to see if it's an 8-bit image needed later for scaling).
    if strcmpi(class(rgbImage), 'uint8')
      % Flag for 256 gray levels.
      eightBit = true;
    else
      eightBit = false;
    end
    if numberOfColorBands == 1
      if isempty(storedColorMap)
        % Just a simple gray level image, not indexed with a stored color map.
        % Create a 3D true color image where we copy the monochrome image into all 3 (R, G, & B) color planes.
        rgbImage = cat(3, rgbImage, rgbImage, rgbImage);
      else
        % It's an indexed image.
        rgbImage = ind2rgb(rgbImage, storedColorMap);
        % ind2rgb() will convert it to double and normalize it to the range 0-1.
        % Convert back to uint8 in the range 0-255, if needed.
        if eightBit
          rgbImage = uint8(255 * rgbImage);
        end
      end
    end
    
    % Display the original image.
    h1 = subplot(3, 4, 1);
    imshow(rgbImage);
    drawnow; % Make it display immediately. 
    if numberOfColorBands > 1 
      title('Original Color Image', 'FontSize', fontSize); 
    else 
      caption = sprintf('Original Indexed Image\n(converted to true color with its stored colormap)');
      title(caption, 'FontSize', fontSize);
      end

      cform = makecform('srgb2lab');
    lab_Image = applycform(im2double(rgbImage),cform);
    
    % Extract out the color bands from the original image
    % into 3 separate 2D arrays, one for each color component.
    LChannel = lab_Image(:, :, 1); 
    aChannel = lab_Image(:, :, 2); 
    bChannel = lab_Image(:, :, 3); 
      % Display the lab images.
    subplot(3, 4, 2);
    imshow(LChannel, []);
    title('L Channel', 'FontSize', fontSize);
    subplot(3, 4, 3);
    imshow(aChannel, []);
    title('a Channel', 'FontSize', fontSize);
    subplot(3, 4, 4);
    imshow(bChannel, []);
    title('b Channel', 'FontSize', fontSize);

  % Get the average lab color value.
  [LMean, aMean, bMean] = GetMeanLABValues(LChannel, aChannel, bChannel, mask);
    Undefined function or variable 'fontSize'.

      LStandard = [82.56,78.43,74.44,73.68];
      aStandard = [1.37,3.82,4.02,5.41];
      bStandard = [12.33,21.35,20.23,23.09];
    
    
    % Create the delta images: delta L, delta A, and delta B.
    deltaL = LChannel - LStandard;
    deltaa = aChannel - aStandard;
    deltab = bChannel - bStandard;
    
    % Create the Delta E image.
    % This is an image that represents the color difference.
    % Delta E is the square root of the sum of the squares of the delta images.
    deltaE = sqrt(deltaL .^ 2 + deltaa .^ 2 + deltab .^ 2);
    
    % Mask it to get the Delta E in the mask region only.
    maskedDeltaE = deltaE .* mask;
    % Get the mean delta E in the mask region
    % Note: deltaE(mask) is a 1D vector of ONLY the pixel values within the masked area.
     meanMaskedDeltaE = mean(deltaE(mask));
    % Get the standard deviation of the delta E in the mask region
    stDevMaskedDeltaE = std(deltaE(mask));
    message = sprintf('The mean LAB = (%.2f, %.2f, %.2f).\nThe mean Delta E in the masked region is %.2f +/- %.2f',...
      LMean, aMean, bMean, meanMaskedDeltaE, stDevMaskedDeltaE);  
    
    % Display the masked Delta E image - the delta E within the masked region only.
    subplot(3, 4, 6);
    imshow(maskedDeltaE, []);
    caption = sprintf('Delta E between image within masked region\nand mean color within masked region.\n(With amplified intensity)');
    title(caption, 'FontSize', fontSize);

  % Display the Delta E image - the delta E over the entire image.
  subplot(3, 4, 7);
  imshow(deltaE, []);
  caption = sprintf('Delta E Image\n(Darker = Better Match)');
  title(caption, 'FontSize', fontSize);

  % Plot the histograms of the Delta E color difference image,
  % both within the masked region, and for the entire image.
  PlotHistogram(deltaE(mask), deltaE, [3 4 8], 'Histograms of the 2 Delta E Images');
  
  message = sprintf('%s\n\nRegions close in color to the color you picked\nwill be dark in the Delta E image.\n', message);
  msgboxw(message);

  % Find out how close the user wants to match the colors.
  prompt = {sprintf('First, examine the histogram.\nThen find pixels within this Delta E (from the average color in the region you drew):')};
  dialogTitle = 'Enter Delta E Tolerance';
  numberOfLines = 1;
  % Set the default tolerance to be the mean delta E in the masked region plus two standard deviations.
  strTolerance = sprintf('%.1f', meanMaskedDeltaE + 3 * stDevMaskedDeltaE);
  defaultAnswer = {strTolerance};  % Suggest this number to the user.
  response = inputdlg(prompt, dialogTitle, numberOfLines, defaultAnswer);
  % Update tolerance with user's response.
  tolerance = str2double(cell2mat(response));

  % Let them interactively select the threshold with the threshold() m-file.
  % (Note: This is a separate function in a separate file in my File Exchange.)
%   threshold(deltaE);
  
  % Place a vertical bar at the threshold location.
  handleToSubPlot8 = subplot(3, 4, 8);  % Get the handle to the plot.
  PlaceVerticalBarOnPlot(handleToSubPlot8, tolerance, [0 .5 0]);  % Put a vertical red line there.
  
  % Find pixels within that delta E.
  binaryImage = deltaE <= tolerance;
  subplot(3, 4, 9);
  imshow(binaryImage, []);
  title('Matching Colors Mask', 'FontSize', fontSize);
  
  % Mask the image with the matching colors and extract those pixels.
  matchingColors = bsxfun(@times, rgbImage, cast(binaryImage, class(rgbImage)));
  subplot(3, 4, 10);
  imshow(matchingColors);
  caption = sprintf('Matching Colors (Delta E <= %.1f)', tolerance);
  title(caption, 'FontSize', fontSize);

  % Mask the image with the NON-matching colors and extract those pixels.
  nonMatchingColors = bsxfun(@times, rgbImage, cast(~binaryImage, class(rgbImage)));
  subplot(3, 4, 11);
  imshow(nonMatchingColors);
  caption = sprintf('Non-Matching Colors (Delta E > %.1f)', tolerance);
  title(caption, 'FontSize', fontSize);

  % Display credits: the MATLAB logo and my name.
  ShowCredits(); % Display logo in plot position #12.
  
  % Alert user that the demo has finished.
  message = sprintf('Done!\n\nThe demo has finished.\nRegions close in color to the color you picked\nwill be dark in the Delta E image.\n');
  msgbox(message);
  
catch ME
  errorMessage = sprintf('Error running this m-file:\n%s\n\nThe error message is:\n%s', ...
    mfilename('fullpath'), ME.message);
  errordlg(errorMessage);
end
return; % from SimpleColorDetection()
% ---------- End of main function ---------------------------------

%----------------------------------------------------------------------------
% Display the MATLAB logo.
function ShowCredits()
try
%   xpklein;
%   surf(peaks(30));
  logoFig = subplot(3, 4, 12);
  caption = sprintf('A MATLAB Demo\nby ImageAnalyst');
  text(0.5,1.15, caption, 'Color','r', 'FontSize', 18, 'FontWeight','b', 'HorizontalAlignment', 'Center') ;
  positionOfLowerRightPlot = get(logoFig, 'position');
  L = 40*membrane(1,25);
  logoax = axes('CameraPosition', [-193.4013 -265.1546  220.4819],...
    'CameraTarget',[26 26 10], ...
    'CameraUpVector',[0 0 1], ...
    'CameraViewAngle',9.5, ...
    'DataAspectRatio', [1 1 .9],...
    'Position', positionOfLowerRightPlot, ...
    'Visible','off', ...
    'XLim',[1 51], ...
    'YLim',[1 51], ...
    'ZLim',[-13 40], ...
    'parent',gcf);
  s = surface(L, ...
    'EdgeColor','none', ...
    'FaceColor',[0.9 0.2 0.2], ...
    'FaceLighting','phong', ...
    'AmbientStrength',0.3, ...
    'DiffuseStrength',0.6, ... 
    'Clipping','off',...
    'BackFaceLighting','lit', ...
    'SpecularStrength',1.1, ...
    'SpecularColorReflectance',1, ...
    'SpecularExponent',7, ...
    'Tag','TheMathWorksLogo', ...
    'parent',logoax);
  l1 = light('Position',[40 100 20], ...
    'Style','local', ...
    'Color',[0 0.8 0.8], ...
    'parent',logoax);
  l2 = light('Position',[.5 -1 .4], ...
    'Color',[0.8 0.8 0], ...
    'parent',logoax);

catch ME
  errorMessage = sprintf('Error running ShowCredits().\n\nThe error message is:\n%s', ...
    ME.message);
  errordlg(errorMessage);
end
return; % from ShowCredits()

%-----------------------------------------------------------------------------
function [xCoords, yCoords, roiPosition] = DrawBoxRegion(handleToImage)
  try
  % Open a temporary full-screen figure if requested.
  enlargeForDrawing = true;
  axes(handleToImage);
  if enlargeForDrawing
    hImage = findobj(gca,'Type','image');
    numberOfImagesInside = length(hImage);
    if numberOfImagesInside > 1
      imageInside = get(hImage(1), 'CData');
    else
      imageInside = get(hImage, 'CData');
    end
    hTemp = figure;
    hImage2 = imshow(imageInside, []);
    [rows columns NumberOfColorBands] = size(imageInside);
    set(gcf, 'Position', get(0,'Screensize')); % Maximize figure.
  end
  
  txtInfo = sprintf('Draw a box over the unstained fabric by clicking and dragging over the image.\nDouble click inside the box to finish drawing.');
  text(10, 40, txtInfo, 'color', 'r', 'FontSize', 24);

        % Prompt user to draw a region on the image.
      msgboxw(txtInfo);
      
      % Erase all previous lines.
      if ~enlargeForDrawing
        axes(handleToImage);
    %     ClearLinesFromAxes(handles);
      end
      
      hBox = imrect;
      roiPosition = wait(hBox);
      roiPosition
      % Erase all previous lines.
      if ~enlargeForDrawing
        axes(handleToImage);
    %     ClearLinesFromAxes(handles);
      end

  xCoords = [roiPosition(1), roiPosition(1)+roiPosition(3), roiPosition(1)+roiPosition(3), roiPosition(1), roiPosition(1)];
  yCoords = [roiPosition(2), roiPosition(2), roiPosition(2)+roiPosition(4), roiPosition(2)+roiPosition(4), roiPosition(2)];

  % Plot the mask as an outline over the image.
  hold on;
  plot(xCoords, yCoords, 'linewidth', 2);
  close(hTemp);
  catch ME
    errorMessage = sprintf('Error running DrawRegion:\n\n\nThe error message is:\n%s', ...
      ME.message);
    WarnUser(errorMessage);
  end
  return; % from DrawRegion
  
%-----------------------------------------------------------------------------
function [mask] = DrawFreehandRegion(handleToImage, rgbImage)
try
  fontSize = 14;
  % Open a temporary full-screen figure if requested.
  enlargeForDrawing = true;
  axes(handleToImage);
  if enlargeForDrawing
    hImage = findobj(gca,'Type','image');
    numberOfImagesInside = length(hImage);
    if numberOfImagesInside > 1
      imageInside = get(hImage(1), 'CData');
    else
      imageInside = get(hImage, 'CData');
    end
    hTemp = figure;
    hImage2 = imshow(imageInside, []);
    [rows columns NumberOfColorBands] = size(imageInside);
    set(gcf, 'Position', get(0,'Screensize')); % Maximize figure.
  end
  
  message = sprintf('Left click and hold to begin drawing.\nSimply lift the mouse button to finish');
  text(10, 40, message, 'color', 'r', 'FontSize', fontSize);

        % Prompt user to draw a region on the image.
      uiwait(msgbox(message));
      
      % Now, finally, have the user freehand draw the mask in the image.
      hFH = imfreehand();

  % Once we get here, the user has finished drawing the region.
  % Create a binary image ("mask") from the ROI object.
  mask = hFH.createMask();
  
  % Close the maximized figure because we're done with it.
  close(hTemp);

  % Display the freehand mask.
  subplot(3, 4, 5);
  imshow(mask);
  title('Binary mask of the region', 'FontSize', fontSize);
  
  % Mask the image.
  maskedRgbImage = bsxfun(@times, rgbImage, cast(mask,class(rgbImage)));
  % Display it.
  subplot(3, 4, 6);
  imshow(maskedRgbImage);
catch ME
  errorMessage = sprintf('Error running DrawFreehandRegion:\n\n\nThe error message is:\n%s', ...
    ME.message);
  WarnUser(errorMessage);
end
return; % from DrawFreehandRegion

%-----------------------------------------------------------------------------
% Get the average lab within the mask region.
function [LMean, aMean, bMean] = GetMeanLABValues(LChannel, aChannel, bChannel, mask)
try
  LVector = LChannel(mask); % 1D vector of only the pixels within the masked area.
  LMean = mean(LVector);
  aVector = aChannel(mask); % 1D vector of only the pixels within the masked area.
  aMean = mean(aVector);
  bVector = bChannel(mask); % 1D vector of only the pixels within the masked area.
  bMean = mean(bVector);
catch ME
  errorMessage = sprintf('Error running GetMeanLABValues:\n\n\nThe error message is:\n%s', ...
    ME.message);
  WarnUser(errorMessage);
end
return; % from GetMeanLABValues

%==========================================================================================================================
function WarnUser(warningMessage)
  uiwait(warndlg(warningMessage));
  return; % from WarnUser()
  
%==========================================================================================================================
function msgboxw(message)
  uiwait(msgbox(message));
  return; % from msgboxw()
  
%==========================================================================================================================
% Plots the histograms of the pixels in both the masked region and the entire image.
function PlotHistogram(maskedRegion, doubleImage, plotNumber, caption)
try
  fontSize = 14;
  subplot(plotNumber(1), plotNumber(2), plotNumber(3)); 

  % Find out where the edges of the histogram bins should be.
  maxValue1 = max(maskedRegion(:));
  maxValue2 = max(doubleImage(:));
  maxOverallValue = max([maxValue1 maxValue2]);
  edges = linspace(0, maxOverallValue, 100);

  % Get the histogram of the masked region into 100 bins.
  pixelCount1 = histc(maskedRegion(:), edges);

  % Get the histogram of the entire image into 100 bins.
  pixelCount2 = histc(doubleImage(:), edges);

  % Plot the  histogram of the entire image.
  plot(edges, pixelCount2, 'b-');
  
  % Now plot the histogram of the masked region.
  % However there will likely be so few pixels that this plot will be so low and flat compared to the histogram of the entire
  % image that you probably won't be able to see it.  To get around this, let's scale it to make it higher so we can see it.
  gainFactor = 1.0;
  maxValue3 = max(max(pixelCount2));
  pixelCount3 = gainFactor * maxValue3 * pixelCount1 / max(pixelCount1);
  hold on;
  plot(edges, pixelCount3, 'r-');
  title(caption, 'FontSize', fontSize);
  
  % Scale x axis manually.
  xlim([0 edges(end)]);
  legend('Entire', 'Masked');
  
catch ME
  errorMessage = sprintf('Error running PlotHistogram:\n\n\nThe error message is:\n%s', ...
    ME.message);
  WarnUser(errorMessage);
end
return; % from PlotHistogram

%=====================================================================
% Shows vertical lines going up from the X axis to the curve on the plot.
function lineHandle = PlaceVerticalBarOnPlot(handleToPlot, x, lineColor)
  try
    % If the plot is visible, plot the line.
    if get(handleToPlot, 'visible')
      axes(handleToPlot);  % makes existing axes handles.axesPlot the current axes.
      % Make sure x location is in the valid range along the horizontal X axis.
      XRange = get(handleToPlot, 'XLim');
      maxXValue = XRange(2);
      if x > maxXValue
        x = maxXValue;
      end
      % Erase the old line.
      %hOldBar=findobj('type', 'hggroup');
      %delete(hOldBar);
      % Draw a vertical line at the X location.
      hold on;
      yLimits = ylim;
      lineHandle = line([x x], [yLimits(1) yLimits(2)], 'Color', lineColor, 'LineWidth', 3);
      hold off;
    end
  catch ME
    errorMessage = sprintf('Error running PlaceVerticalBarOnPlot:\n\n\nThe error message is:\n%s', ...
      ME.message);
    WarnUser(errorMessage);
end
  return;  % End of PlaceVerticalBarOnPlot

[Walter Roberson]

What error are you observing? We do not have your image so we cannot test for ourselves.

In R2014a, imshow() was still part of the Image Processing Toolbox, so you would need that toolbox.

[Rifayet Ashraf]

Image processing toolbox already there one of the example error I am attaching here. I am attaching my image also.

[Rifayet Ashraf]

Actually my task is-

1. Get the image using raspberry pi camera.
2. Import the image to Matlab code.
3. Do the comparison with a shade database and find the best match from the database.

Don't know how to create the database using the photos attached.

Answer 1

[Walter Roberson]

At line 156, catch ME is outside of any try. Judging from the indentation there should be a try between lines 4 and 5.

The code uses functions within a script file. That was not permitted until R2016b. Starting in R2016b it is permitted, but the functions are required to have end statements matching their function line, which is not the case in this code. You will need to write each of the function into its own .m file for R2014a, or else you will need to restore the function line that you probably deleted from the beginning of the code. The code appears to be a modified version of one of Image Analyst's demos.

Notice how near line 65 you have the code line

       Undefined function or variable 'fontSize'.

so you appear to have copied and pasted the code from somewhere.

[Rifayet Ashraf]

If I change the version into R2016b, is it gonna solve the problem of the "Function"?

About the (Undefined function or variable 'fontSize'), since I copy the code, I might copy wrongly. I tried to removed the line but it is not improving any error.

Another question is , how to create a database by using those image I shared previously. And also want to know how to add the database code into this shade code?

[Walter Roberson]

"If I change the version into R2016b, is it gonna solve the problem of the "Function"?"

No. However, if you went through the code and everywhere there is a function you added an end corresponding to the function line, then the result should be something that would be valid as a single file for R2016b and later.

Or... you could just add a single function line to the top, which would make it into a function file instead of a script.

"how to create a database by using those image I shared previously"

There are multiple ways. If you were using R2016a or later you could use the imageDatastore function. (If you look closely at the release date you will see it says R2015b rather than R2016a: however in R2015b, imageDatastore was only a class which could not yet be called as a function.)

[Rifayet Ashraf]

After I install the R2016b, I will give you some update on it by few hours.

[Image Analyst]

Why install that? If you're going to install a later version, why not install the latest, which is R2017b?