MATLAB: Fitting lines and polynomialon on edge after edge extraction and finding a certain distance

curve fittingimage processingImage Processing ToolboxlineMATLAB

I got the following edge after extracting it from a image which has been provided by me in attachmnent. I need to fit a red line along the lower edge and green horizontal line as shown in 2nd figure and find the distance.

What approach should I use???

The desired result I seek??

Best Answer

Really easy. Call bwconvhull(bw, 'union'). Then scan column-by-column using find() to get the last/lowest white point. Then fit those bottom rows to a quadratic with polyfit(), if you want - it's optional because the curve is not really needed to find the height of the last column. Then you simple need to find the last column where there is some white and subtract it from the max value. Something like (untested)

mask = bwconvhull(mask, 'union');
[rows, columns] = size(mask);
bottomRows = zeros(1, columns);
for col = 1 : columns
    thisCol = mask(:, col);
    r = find(thisCol, 1, 'last');
    if ~isempty(r)
        bottomRows(col) = r;
    end
end
lastColumn = find(bottomRows > 0, 1, 'last');
bottomLine = max(bottomRows);
yline(bottomLine, 'Color', 'g', 'LineWidth', 2)
distance = bottomLine - bottomRows(lastColumn)
% Optional fitting
goodIndexes = bottomRows > 0;
c = 1:columns;
x = c(goodIndexes);
y = bottomRows(goodIndexes);
coefficients = polyfit(x, y, 2);
xFit = c;
yFit = polyval(coefficients, xFit);
hold on;
plot(xFit, yFit, 'r-', 'LineWidth', 2)
yLast = yFit(lastColumn);
plot(lastColumn, yLast, 'r+', 'MarkerSize', 30)
fittedDistance = bottomLine - yLast 
% Will be different than other distance because the other one was actual 
% and this one is from the regression.

Related Solutions

MATLAB: Finding distances between irregular vertical lines for all pixel rows and outputting values

Try 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 = 20;
%===============================================================================
% Read in a standard MATLAB gray scale demo image.
folder = pwd;
baseFileName = '160ulpmin_1 Export.png';
% Get the full filename, with path prepended.
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);
% Get 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 > 1
  % It's not really gray scale like we expected - it's color.
  % Use weighted sum of ALL channels to create a gray scale image.
  grayImage = rgb2gray(grayImage); 
  % ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
  % which in a typical snapshot will be the least noisy channel.
  % grayImage = grayImage(:, :, 2); % Take green channel.
end
% Display the image.

subplot(2, 2, 1);
imshow(grayImage);
title('Original Grayscale Image', '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') 
% Get a binary image of the black lines
binaryImage = grayImage > 128;
[labeledImage, numBlobs] = bwlabel(binaryImage);
% Display the image.
subplot(2, 2, 2);
imshow(binaryImage, []);
axis on;
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Find width at every row
widths = zeros(rows, 1);
for row = 1 : rows
  thisRow = binaryImage(row, :);
  leftPixel = find(thisRow, 1, 'first');
  rightPixel = find(thisRow, 1, 'last');
  if isempty(leftPixel) || isempty(rightPixel)
    continue; % Skip lines where there is no white pixel.
  end
  widths(row) = rightPixel - leftPixel;  % Add 1 if you want whole pixels instead of pixel center-to-pixel center.
end
% Display the plot.
subplot(2, 2, 3:4);
plot(widths, 'b-', 'LineWidth', 2);
grid on;
xlabel('Row', 'FontSize', fontSize);
ylabel('Width in pixels', 'FontSize', fontSize);
title('Widths', 'FontSize', fontSize);

MATLAB: Application of polyfit() on certain pixels.

Ron:

Your problem came before that image. It came when you thought you should do an edge detection. Like most beginners, you thought that because you can see edges in the image, that edge detection must be the first step. It is usually not. What you should have done was a color segmentation and then find the bottom's edge and then fit a curve to it and get the distance. Here is corrected code:

% Demo to find distances.  By Image Analyst, May 5, 2020.
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;
fprintf('Beginning to run %s.m ...\n', mfilename);
%-----------------------------------------------------------------------------------------------------------------------------------
% Read in image.
folder = pwd;
baseFileName = 'warped_image2.jpeg';
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
rgbImage = imread(fullFileName);
[rows, columns, numberOfColorChannels] = size(rgbImage);
% Display the test image full size.
subplot(2, 1, 1);
imshow(rgbImage, []);
axis('on', 'image');
caption = sprintf('Reference 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.
hFig1 = gcf;
hFig1.Units = 'Normalized';
hFig1.WindowState = 'maximized';
% 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.
hFig1.Name = 'Demo by Image Analyst';
[mask, maskedRGBImage] = createMask(rgbImage);
% Fill holes
mask = imfill(mask, 'holes');
% Smooth the mask by filtering
windowSize = 7; % An odd number.
f = ones(windowSize)/windowSize^2;
mask = imfilter(mask, f);
% Display the distance image.
subplot(2, 1, 2);
imshow(mask, []);
axis('on', 'image');
caption = sprintf('Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
colorbar;
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Scan getting the bottom row.
bottomRows = zeros(1, columns);
for col = 1 : columns
    thisCol = mask(:, col);
    r = find(thisCol, 1, 'last');
    if ~isempty(r)
        bottomRows(col) = r;
    end
end
lastColumn = find(bottomRows > 0, 1, 'last')
bottomLine = max(bottomRows)
hold on;
yline(bottomLine, 'Color', 'g', 'LineWidth', 2)
plot(lastColumn, bottomRows(lastColumn), 'mo', 'MarkerSize', 15, 'LineWidth', 2)
text(lastColumn, bottomRows(lastColumn), 'Right most point   ', 'HorizontalAlignment', 'right', 'Color', 'm', 'FontSize', 15, 'FontWeight', 'bold');
distance = bottomLine - bottomRows(lastColumn)
% Fitting
goodIndexes = bottomRows > 0;
c = 1:columns;
x = c(goodIndexes);
y = bottomRows(goodIndexes);
coefficients = polyfit(x, y, 2);
xFit = c;
yFit = polyval(coefficients, xFit);
plot(xFit, yFit, 'r-', 'LineWidth', 2)
yLast = yFit(lastColumn);
plot(lastColumn, yLast, 'r+', 'MarkerSize', 50, 'LineWidth', 2)
text(lastColumn, yLast, 'Fitted y at Right most point      ', 'HorizontalAlignment', 'right', 'Color', 'r', 'FontSize', 15, 'FontWeight', 'bold');
fittedDistance = bottomLine - yLast 
caption = sprintf('Magenta-to-green distance = %.1f. Red-to-green distance = %.1f', distance, fittedDistance);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
% Will be different than other distance because the other one was actual 
% and this one is from the regression.
fprintf('Done running %s.m ...\n', mfilename);
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 25-Jul-2020
%------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2lab(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 5.530;
channel1Max = 99.753;
% Define thresholds for channel 2 based on histogram settings
channel2Min = -14.832;
channel2Max = 45.687;
% Define thresholds for channel 3 based on histogram settings
channel3Min = -73.763;
channel3Max = -28.389;
% 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

If you can, you should use a black background, not white. And you should use crossed polarizers to knock out the specular reflections (white glints). Finally you should adjust your camera angle to have the optic axis be normal to the bottom plane of that blue slab. Ideally you should be using a "telecentric" lens, not a regular lens.

Regarding what you did wrong with the red curve and polyfit(), it looks likely you swapped x and y. Remember, images are not indexed like mask(x, y). They are indexed mask(row, column) which is mask(y, x). This is another extremely common beginner mistake. It looks like you may have swapped x and y in polyfit().

Best Answer

Related Solutions

MATLAB: Finding distances between irregular vertical lines for all pixel rows and outputting values

MATLAB: Application of polyfit() on certain pixels.

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