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How to draw vertical and horizontal histogram of an image ?

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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 ?

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Accepted Answer

Image Analyst
Image Analyst on 6 Oct 2018
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().

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Sudipto Chaki
Sudipto Chaki on 6 Oct 2018
Thanks for your answer. But, is it possible to extract Rectangular ROI based on vertical or horizontal profile?
Sudipto Chaki
Sudipto Chaki on 6 Oct 2018
Basically I need to extract the following ROI automatically.

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More Answers (1)

Image Analyst
Image Analyst on 6 Oct 2018
Try this:
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
workspace; % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;
%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = '6.jpg';
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.
[rows, columns, numberOfColorChannels] = size(rgbImage)
% Display image.
subplot(2, 2, 1);
imshow(rgbImage, []);
impixelinfo;
axis on;
caption = sprintf('Original Color Image\n%s', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
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')
drawnow;
[mask, maskedRGBImage] = createMask(rgbImage);
% Extract the largest blob only. That will be the hand.
mask = bwareafilt(mask, 1);
% Get the convex hull to get rid of boundary noise (wiggles).
mask = bwconvhull(mask);
% Display the mask image.
subplot(2, 2, 2);
imshow(mask);
title('Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis on;
drawnow;
% Mask the image using bsxfun() function to multiply the mask by each channel individually.
maskedRgbImage = bsxfun(@times, rgbImage, cast(mask, 'like', rgbImage));
% Crop the image
[maskRows, maskColumns] = find(mask);
row1 = min(maskRows);
row2 = max(maskRows);
col1 = min(maskColumns);
col2 = max(maskColumns);
% Plot the box
xBox = [col1, col2, col2, col1, col1];
yBox = [row1, row1, row2, row2, row1];
hold on;
plot(xBox, yBox, 'r-', 'LineWidth', 2);
% Crop the masked image.
maskedRgbImage = maskedRgbImage(row1:row2, col1:col2, :);
% Get the dimensions of the image.
[maskRows, maskColumns, numberOfColorChannels] = size(maskedRgbImage)
% Display the image.
subplot(2, 2, 3);
imshow(maskedRgbImage, []);
impixelinfo;
title('Masked Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis on;
drawnow;
% Crop the numbers out. From the circular mask, the numbers are between
% 17.7% and 25.9% of the height of the image, and between
% 26.6 and 40.2% of the width of the image
row1 = round(.244 * maskRows)
row2 = round(.357 * maskRows)
col1 = round(.212 * maskColumns)
col2 = round(.526 * maskColumns)
% Plot the box
xBox = [col1, col2, col2, col1, col1];
yBox = [row1, row1, row2, row2, row1];
hold on;
plot(xBox, yBox, 'r-', 'LineWidth', 2);
maskedRgbImage = maskedRgbImage(row1:row2, col1:col2, :);
% Display the image.
subplot(2, 2, 4);
imshow(maskedRgbImage, []);
impixelinfo;
title('Masked Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis on;
drawnow;
fprintf('DONE!\n');
uiwait(helpdlg('Done!'));
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 06-Oct-2018
%------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.201;
channel1Max = 0.000;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.000;
channel2Max = 0.236;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.303;
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

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Sudipto Chaki
Sudipto Chaki on 7 Oct 2018
Ok, thanks. I need to convert the following digit image into (3*2) blocks. Then, I want to find out the horizontal and vertical edges in each block separately if exists. Is it possible and how?
Sudipto Chaki
Sudipto Chaki on 7 Oct 2018
How to convert the digit image into (3*2) blocks where I can check vertical and horizontal edges using imgradientxy()? Actually, I need to check if vertical or horizontal edges exists in each block? If exists I need to return binary value 1.

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