% Demo by Image Analyst
% https://www.mathworks.com/matlabcentral/answers/2044247-recognize-edges-in-mosaic-like-background-draw-horizontal-lines-and-save-line-coordinates?s_tid=srchtitle
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 = 16;
markerSize = 20;
%--------------------------------------------------------------------------------------------------------
% READ IN TEST IMAGE
folder = [];
baseFileName = 'sample 1.jpg';
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
grayImage = imread(fullFileName);
%--------------------------------------------------------------------------------------------------------
% Display the image.
subplot(2, 2, 1);
imshow(grayImage, []);
impixelinfo;
axis('on', 'image');
title('Original Gray Scale Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Update the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage)
if numberOfColorChannels == 3
grayImage = rgb2gray(grayImage);
end
% Maximize window.
g = gcf;
g.WindowState = 'maximized';
g.Name = 'Demo by Image Analyst';
g.NumberTitle = 'off';
drawnow;
%--------------------------------------------------------------------------------------------------------
% Get the mean vertical profile of the standard deviation of each row.
verticalProfile = std(single(grayImage), 0, 2);
% Smooth out noise but leave big dips
verticalProfile = movmedian(verticalProfile,61);
subplot(2, 2, 2);
plot(verticalProfile, 'b-', 'LineWidth', 2);
title('Standard Deviation Row-by-Row', 'FontSize', fontSize, 'Interpreter', 'None');
xlabel('Row of Image', 'FontSize', fontSize, 'Interpreter', 'None');
ylabel('Standard Deviation', 'FontSize', fontSize, 'Interpreter', 'None');
grid on;
drawnow;
%--------------------------------------------------------------------------------------------------------
% Get mask by thresholding at 62.
grayRegions = verticalProfile' <= 62;
% Get tops
topLines = strfind(grayRegions, [0, 1])
% Get bottoms
bottomLines = strfind(grayRegions, [1, 0])
subplot(2, 2, 3);
imshow(grayImage, []);
axis('on', 'image');
hold on;
% Draw line at edges
for k = 1 : numel(topLines)
yline(topLines(k), 'Color', 'y', 'LineWidth', 3);
end
for k = 1 : numel(bottomLines)
yline(bottomLines(k), 'Color', 'y', 'LineWidth', 3);
end
title('Edges Identified', 'FontSize', fontSize, 'Interpreter', 'None');
