MATLAB: How to draw vertical and horizontal histogram of an image

horizontal and vertical histogram

I need to draw vertical and horizontal histogram of a gray scale image to find out the rectangular ROI of my image. Is it possible ?

Best Answer

I wouldn't call them histograms but I think you are referring to the mean vertical or horizontal profile that you get by summing or averaging gray levels horizontally or vertically. To do that you'd do:

verticalProfile = sum(grayImage, 2);
horizontalProfile = sum(grayImage, 1);

or you can use mean() instead of sum().

Related Solutions

MATLAB: How to separate the whole lip image into upper and lower part using code

Do you mean like this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 15;
%===============================================================================

% Get the name of the image the user wants to use.
baseFileName = 'originalimage.jpg';
% Get the full filename, with path prepended.
folder = pwd
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
  % The file doesn't exist -- didn't find it there in that folder.
  % Check the entire search path (other folders) for the file by stripping off the folder.
  fullFileNameOnSearchPath = baseFileName; % No path this time.
  if ~exist(fullFileNameOnSearchPath, '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
%===============================================================================
% Read in demo image.
rgbImage = imread(fullFileName);
% Get the dimensions of the image.
[imageRows, imageColumns, numberOfColorChannels] = size(rgbImage);
% Display the original image.
subplot(3, 3, 1);
imshow(rgbImage, []);
axis on;
caption = sprintf('Original Color Image, %s', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);
% Get rid of tool bar and pulldown menus that are along top of figure.
set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Crop the image
rgbImage = rgbImage(29:391, 87:762, :);
% Convert to HSV color space so we can segment the saturation channel.
hsvImage = rgb2hsv(rgbImage);
sImage = hsvImage(:, :, 2);
% Display the image.





subplot(3, 3, 2);
imshow(sImage, []);
axis on;
caption = sprintf('Saturation Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Display the histogram
subplot(3, 3, 3);
histogram(sImage);
grid on;
title('Histogram of Saturation Image', 'FontSize', fontSize);
% Threshold the image
saturationThreshold = 0.15;
mask = sImage > saturationThreshold;
% Fill holes.
mask = imfill(mask, 'holes');
% Extract the two largest blobs only.
mask = bwareafilt(mask, 2);
% Put a red line at the threshold.
line([saturationThreshold, saturationThreshold], ylim, 'Color', 'r', 'LineWidth', 3);
% Display the image.
subplot(3, 3, 4);
imshow(mask, []);
axis on;
caption = sprintf('Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Give each blob an ID number.
labeledImage = bwlabel(mask);
% Get the top and bottom mask
topMask = ismember(labeledImage, 1);
bottomMask = ismember(labeledImage, 2);
% Display the image.
subplot(3, 3, 5);
imshow(topMask, []);
axis on;
caption = sprintf('Top Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Display the image.
subplot(3, 3, 6);
imshow(bottomMask, []);
axis on;
caption = sprintf('Bottom Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Mask the original RGB image and display.
% Mask the image using bsxfun() function
topMaskedRgbImage = bsxfun(@times, rgbImage, cast(topMask, 'like', rgbImage));
bottomMaskedRgbImage = bsxfun(@times, rgbImage, cast(bottomMask, 'like', rgbImage));
% Display the image.
subplot(3, 3, 7);
imshow(topMaskedRgbImage, []);
axis on;
caption = sprintf('Top Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Display the image.
subplot(3, 3, 8);
imshow(bottomMaskedRgbImage, []);
axis on;
caption = sprintf('Bottom Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;

MATLAB: What is the fit method to exclude the shadow?

Try this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clearvars;
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;
%=======================================================================================
% Read in image.
fullFileName = fullfile(pwd, '63.jpg');
[folder, baseFileName, ext] = fileparts(fullFileName);
rgbImage = imread(fullFileName);
% Shrink it to speed it up
% rgbImage = imresize(rgbImage, 0.75);
% Get the dimensions of the image.
[rows, columns, numberOfColorChannels] = size(rgbImage);
% Display the original image.
subplot(2, 2, 1);
imshow(rgbImage, []);
axis on;
caption = sprintf('Original Color Image "%s"', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.


% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0.05 1 0.95]);
% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')
% Get mask for outer gray, and inner blue parts of the wheel by doing color segmentations.
[mask, maskedRGBImage] = createMask(rgbImage);
% Clean up noise by filling holes and taking largest blob only.
mask = imfill(mask, 'holes');
mask = bwareafilt(mask, 1);
% Display the mask image.
subplot(2, 2, 2);
imshow(mask);
axis on;
title('Mask, binary image', 'FontSize', fontSize, 'Interpreter', 'None');
% Mask the image and show the masked image.
subplot(2, 2, 3);
imshow(maskedRGBImage, []);
axis on;
title('Masked RGB image', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Display the original image with mask boundary over it.
subplot(2, 2, 4);
imshow(rgbImage, []);
axis on;
caption = sprintf('Color Image with Boundary');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Plot boundaries
boundaries = bwboundaries(mask);
hold on;
numberOfBoundaries = size(boundaries, 1);
for k = 1 : numberOfBoundaries
  thisBoundary = boundaries{k};
  plot(thisBoundary(:,2), thisBoundary(:,1), 'r', 'LineWidth', 3);
end
hold off;
function [BW,maskedRGBImage] = createMask(RGB)
%createMask  Threshold RGB image using auto-generated code from colorThresholder app.
%  [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
%  auto-generated code from the colorThresholder app. The colorspace and
%  range for each channel of the colorspace were set within the app. The
%  segmentation mask is returned in BW, and a composite of the mask and
%  original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 20-Aug-2018
%------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.959;
channel1Max = 0.099;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.194;
channel2Max = 1.000;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.410;
channel3Max = 1.000;
% Create mask based on chosen histogram thresholds
sliderBW = ( (I(:,:,1) >= channel1Min) | (I(:,:,1) <= channel1Max) ) & ...
  (I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
  (I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image.
maskedRGBImage = RGB;
% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end

Notes: It's not perfect because you don't have good control over your image capture situation. Get rid of shadows and background clutter to get a better masking.

Best Answer

Related Solutions

MATLAB: How to separate the whole lip image into upper and lower part using code

MATLAB: What is the fit method to exclude the shadow?

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