MATLAB: Boundary tracing in image

bwboundariesedge detectionimage analysisImage Processing Toolbox

Hello folks,

I am trying to trace the boundaries of a binary edge detected image to the point that I can export the file as polylines into ArcGIS. So far, I have converted the image to a binary image and identified the edges. I've tried to use both bwtraceboundary and bwboundaries to identify the edge outlines and then export this file with polylines, but am not having any luck. The original image is attached as is the code to convert the image to a binary edge-detected image. Any help is much appreciated!

clear
RGB=imread('DJI_0022.jpg'); %inputs image
I=rgb2gray(RGB); %convers to grayscale
figure
imshow(I)
BW1 = edge(I,'Canny',0.6);
imshow(BW1)

Best Answer

After Canny, those blobs are single pixel wide blobs, so it makes no sense to call bwboundaries() on them. That would just simply give you the same coordinates you already have, any maybe even doubled up as it goes to one end and back again. I think you want to use regionprops and ask for PixelList.

rgbImage = imread('DJI_0022.jpg'); %inputs image
hFig = figure;
subplot(2, 2, 1);
imshow(rgbImage)
axis('on', 'image');
impixelinfo;
title('Original RGB Image', 'FontSize', 20);
grayImage = rgb2gray(rgbImage); %convers to grayscale
subplot(2, 2, 2);
imshow(grayImage)
axis('on', 'image');
impixelinfo;
title('Gray Scale Image', 'FontSize', 20);
edgeImage = edge(grayImage, 'Canny', 0.6);
subplot(2, 2, 3);
imshow(edgeImage)
axis('on', 'image');
title('Canny Edge Image', 'FontSize', 20);
hFig.WindowState = 'maximized';
drawnow;
% Get coordinates.
props = regionprops(edgeImage, 'PixelList');
for k = 1 : length(props)
	thisList = props(k).PixelList;
	fprintf('\nFor blob #%d of %d:\n    ', k, length(props))
	for k2 = 1 : size(thisList, 1)
		thisx = thisList(k2, 1);
		thisy = thisList(k2, 2);
		fprintf('(%d, %d), ', thisx, thisy);
	end
end

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MATLAB: Binary Image – Black region detection

Mohsina, 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 short g;
format compact;
fontSize = 25;
%===============================================================================

% Get the name of the image the user wants to use.
baseFileName = 'image1.png';
% Get the full filename, with path prepended.
folder = []; % Determine where demo folder is (works with all versions).
fullFileName = fullfile(folder, baseFileName);
%===============================================================================
% Read in a demo image.
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, []);
axis on;
axis image;
caption = sprintf('Original Gray Scale Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo();
% 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;
% Create binary image of the black blobs from grayscale image.
binaryImage = grayImage == 0;
% Get rid of the background.
binaryImage = imclearborder(binaryImage);
% Display the image.
subplot(2, 2, 2);
imshow(binaryImage, []);
axis on;
axis image;
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Label the blobs
[labeledImage, numBlobs] = bwlabel(binaryImage);
% Display the image.
subplot(2, 2, 2);
imshow(binaryImage, []);
axis on;
axis image;
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Let's assign each blob a different color to visually show the user the distinct blobs.
coloredLabels = label2rgb (labeledImage, 'hsv', 'k', 'shuffle'); % pseudo random color labels
% coloredLabels is an RGB image.  We could have applied a colormap instead (but only with R2014b and later)
subplot(2, 2, 3);
imshow(coloredLabels);
axis on;
axis image; % Make sure image is not artificially stretched because of screen's aspect ratio.
caption = sprintf('Pseudo colored labels, from label2rgb().');
title(caption, 'FontSize', fontSize);
drawnow;
% Make measurements of bounding box.
props = regionprops(labeledImage, 'BoundingBox');
% Display the image.
subplot(2, 2, 4);
imshow(binaryImage, []);
axis on;
axis image;
title('Binary Image with Boxes', 'FontSize', fontSize, 'Interpreter', 'None');
% Display the bounding boxes around them.
hold on;
for k = 1 : numBlobs
  thisBoundingBox = props(k).BoundingBox
  rectangle('Position', thisBoundingBox, ...
    'EdgeColor', 'c', 'LineWidth', 2);
end

MATLAB: How to overlay a google earth image with a quiver plot

If you have a map image of your area of interest, you could plot and scale the map coordinates using the imagesc function after reading the image in with the imread function. Furthermore, if you have known points of reference on the map and know the scale, you can simply plot your quiver plot directly over the map image!

Here is an extremely basic outline of how your code could look. The coordinates are up to you to fill in, of course:

% Import map image
mapImage = imread('map.jpg');
imagesc(xMin:xMax,yMin:yMax,mapImage);
hold on;
% Overlay the quiver plot
quiver(x,y,dx,dy);

The primary trick here is to ensure your scales of the map and your quiver plot are aligned. I am also assuming that you will be plotting over a relatively small area such that map projection/transformations are not an issue. I would recommend brushing up on projections, just in case:

http://en.wikipedia.org/wiki/Map_projection

You could also check out the MATLAB mapping toolbox that helps make georeferencing more straightforward.

Hope this helps to get you started!

Best Answer

Related Solutions

MATLAB: Binary Image – Black region detection

MATLAB: How to overlay a google earth image with a quiver plot

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