remove undesired regions before making grey scale image to binary and area calculation

Hi,

This is my first task using Matlab.

I'm hoping to analyze the percentage dark area in my greyscale image. How can I mask some undesired regions in the image before making binary images for area calculation? Below is my code which didn't work

imdir = 'C:\Users\wkuo7\Documents\MATLAB\';
imfile1 = '1103.tif';
I1 = imread([imdir, imfile1]);
I2=imshow(I1);
I3 = roipoly; %and then I draw an ROI and right click to create mask%
I4=imshow(I3); % at here I saw binary image of my ROI (white) and rest (dark)%
H = fspecial('unsharp');
I5 = roifilt2(H,I2,I4);
figure, imshow(I5) %at here I saw figure window pop up, but no image.

below is the code which worked to give me the percentage dark area, but this one has no masking yet.

imdir = 'C:\Users\wkuo7\Documents\MATLAB\';
imfile1 = '1103.tif';
I1 = imread([imdir, imfile1]);
I2 = imcrop(I1,[1 1 1424 845]);
BW1 = roicolor(I2,0,1000); 
BW2 = roicolor(I2,100,1000); imshow(BW2);
percentage = 1 - bwarea(BW2)/bwarea(BW1)

Thank you very much!

[Walter Roberson]

Remember that percentage needs to be multiplied by 100.

[himey]

You're right! Thanks for reminding!

Answer 1

[Image Analyst]

Yeah, your code won't work. The first code would sharpen edges, and the second just gets the ratio of the number of pixels that have a gray level of exactly 100 to the number of pixels that have a gray level of exactly 0.

See my freehand masking demo. You can use this to zero out some hand drawn portion of your image. After masking out the undesired areas, you can then take the histogram and get the ratios you want.

% Demo to have the user freehand draw an irregular shape over
% a gray scale image, have it extract only that part to a new image,
% and to calculate the mean intensity value of the image within that shape.
% Also calculates the perimeter, centroid, and center of mass (weighted centroid).

% Change the current folder to the folder of this m-file.
if(~isdeployed)
  cd(fileparts(which(mfilename)));
end
clc;  % Clear command window.
clear;  % Delete all variables.
close all;  % Close all figure windows except those created by imtool.
imtool close all;  % Close all figure windows created by imtool.
workspace;  % Make sure the workspace panel is showing.
fontSize = 16;

% Read in a standard MATLAB gray scale demo image.
folder = fullfile(matlabroot, '\toolbox\images\imdemos');
baseFileName = 'cameraman.tif';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
  % File doesn't exist -- didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
  if ~exist(fullFileName, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
grayImage = imread(fullFileName);
imshow(grayImage, []);
axis on;
title('Original Grayscale Image', 'FontSize', fontSize);
set(gcf, 'Position', get(0,'Screensize')); % Maximize figure.
message = sprintf('Left click and hold to begin drawing.\nSimply lift the mouse button to finish');
uiwait(msgbox(message));
hFH = imfreehand();
% Create a binary image ("mask") from the ROI object.
binaryImage = hFH.createMask();
xy = hFH.getPosition;

% Now make it smaller so we can show more images.
subplot(2, 3, 1);
imshow(grayImage, []);
axis on;
drawnow;
title('Original Grayscale Image', 'FontSize', fontSize);

% Display the freehand mask.
subplot(2, 3, 2);
imshow(binaryImage);
axis on;
title('Binary mask of the region', 'FontSize', fontSize);

% Label the binary image and computer the centroid and center of mass.
labeledImage = bwlabel(binaryImage);
measurements = regionprops(binaryImage, grayImage, ...
    'area', 'Centroid', 'WeightedCentroid', 'Perimeter');
area = measurements.Area
centroid = measurements.Centroid
centerOfMass = measurements.WeightedCentroid
perimeter = measurements.Perimeter

% Calculate the area, in pixels, that they drew.
numberOfPixels1 = sum(binaryImage(:))
% Another way to calculate it that takes fractional pixels into account.
numberOfPixels2 = bwarea(binaryImage)

% Get coordinates of the boundary of the freehand drawn region.
structBoundaries = bwboundaries(binaryImage);
xy=structBoundaries{1}; % Get n by 2 array of x,y coordinates.
x = xy(:, 2); % Columns.
y = xy(:, 1); % Rows.
subplot(2, 3, 1); % Plot over original image.
hold on; % Don't blow away the image.
plot(x, y, 'LineWidth', 2);
drawnow; % Force it to draw immediately.

% Burn line into image by setting it to 255 wherever the mask is true.
burnedImage = grayImage;
burnedImage(binaryImage) = 255;
% Display the image with the mask "burned in."
subplot(2, 3, 3);
imshow(burnedImage);
axis on;
caption = sprintf('New image with\nmask burned into image');
title(caption, 'FontSize', fontSize);

% Mask the image and display it.
% Will keep only the part of the image that's inside the mask, zero outside mask.
blackMaskedImage = grayImage;
blackMaskedImage(~binaryImage) = 0;
subplot(2, 3, 4);
imshow(blackMaskedImage);
axis on;
title('Masked Outside Region', 'FontSize', fontSize);
% Calculate the mean
meanGL = mean(blackMaskedImage(binaryImage));

% Put up crosses at the centriod and center of mass
hold on;
plot(centroid(1), centroid(2), 'r+', 'MarkerSize', 30, 'LineWidth', 2);
plot(centerOfMass(1), centerOfMass(2), 'g+', 'MarkerSize', 20, 'LineWidth', 2);

% Now do the same but blacken inside the region.
insideMasked = grayImage;
insideMasked(binaryImage) = 0;
subplot(2, 3, 5);
imshow(insideMasked);
axis on;
title('Masked Inside Region', 'FontSize', fontSize);

% Now crop the image.
leftColumn = min(x);
rightColumn = max(x);
topLine = min(y);
bottomLine = max(y);
width = rightColumn - leftColumn + 1;
height = bottomLine - topLine + 1;
croppedImage = imcrop(blackMaskedImage, [leftColumn, topLine, width, height]);
% Display cropped image.
subplot(2, 3, 6);
imshow(croppedImage);
axis on;
title('Cropped Image', 'FontSize', fontSize);

% Put up crosses at the centriod and center of mass
hold on;
plot(centroid(1)-leftColumn, centroid(2)-topLine, 'r+', 'MarkerSize', 30, 'LineWidth', 2);
plot(centerOfMass(1)-leftColumn, centerOfMass(2)-topLine, 'g+', 'MarkerSize', 20, 'LineWidth', 2);

% Report results.
message = sprintf('Mean value within drawn area = %.3f\nNumber of pixels = %d\nArea in pixels = %.2f\nperimeter = %.2f\nCentroid at (x,y) = (%.1f, %.1f)\nCenter of Mass at (x,y) = (%.1f, %.1f)\nRed crosshairs at centroid.\nGreen crosshairs at center of mass.', ...
meanGL, numberOfPixels1, numberOfPixels2, perimeter, ...
centroid(1), centroid(2), centerOfMass(1), centerOfMass(2));
msgbox(message);

[himey]

Thank you! The imfreehand works. Is there a way to do multiple masks on the same image? Below is my updated code which works with single mask.

imdir = 'C:\Users\wkuo7\Documents\MATLAB\'; imfile1 = '1103.tif'; I1 = imread([imdir, imfile1]); imshow(I1, []); axis on; hFH = imfreehand(); I2 = hFH.createMask(); I3 = I1; I3(I2) = 0; imshow(I3); axis on; I6 = imcrop(I3,[1 1 1424 845]); I4 = roicolor(I6,1,1000); I5 = roicolor(I6,100,1000); imshow(I5); percentage = 100 - bwarea(I5)/bwarea(I4)*100

[Image Analyst]

Sure. Just repeat it and OR the second mask in with the first mask.

Answer 2

[Walter Roberson]

I2=imshow(I1);

stores the handle of the image into I2, not the image array. So in your filter, use I1 not I2.

[himey]

Thank you! I changed it into

I5 = roifilt2(H,I1,I4);

 but got the following

Error using roifilt2>parse_inputs (line 130) Image and binary mask must be the same size.

Error in roifilt2 (line 43) [H, J, BW, params, fcnflag] = parse_inputs(varargin{:});

[Walter Roberson]

What does size(I1) and size(I4) report?