I have an image with multiple irregularly shaped blobs. Is it possible to find the dimensions (ie max length, width etc) and area of each blob?
MATLAB: How to find the dimensions and area of an irregularly shaped region in an image
image analysisImage Processing Toolboxregionprops
Related Solutions
Convert to grayscale and then threshold and find the bounding box
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
imtool close all; % Close all imtool figures.
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 the color image.
folder = pwd;baseFileName = 'm2.bmp';% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);if ~exist(fullFileName, 'file') % Didn't find it there. Check the search path for it.
fullFileName = baseFileName; % No path this time.
if ~exist(fullFileName, 'file') % Still didn't find it. Alert user.
errorMessage = sprintf('Error: %s does not exist.', fullFileName); uiwait(warndlg(errorMessage)); return; endendrgbImage = imread(fullFileName);% Get the dimensions of the image. numberOfColorBands should be = 3.
[rows, columns, numberOfColorBands] = size(rgbImage);% Display the original color image.
subplot(2, 3, 1);imshow(rgbImage, []);axis on;title('Original Color Image', 'FontSize', fontSize);drawnow;% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);% Histogram the red channel, but there is a huge spike at 255 so let's not count those.
subplot(2, 3, 2);grayImage = rgb2gray(rgbImage);imshow(grayImage, []);title('Gray Scale version', 'FontSize', fontSize);subplot(2, 3, 3);histogram(grayImage(grayImage<255))grid on;title('Histogram of Gray Scale Image', 'FontSize', fontSize);someThresholdValue = 150;binaryImage = grayImage > someThresholdValue;% Take largest blob
binaryImage = bwareafilt(binaryImage, 1);subplot(2, 3, 4);imshow(binaryImage);grid on;title('Binary Image', 'FontSize', fontSize);% Label the binary image.
labeledImage = bwlabel(binaryImage);props = regionprops(labeledImage, 'BoundingBox');bbox = props.BoundingBoxcroppedImageRGB = imcrop(rgbImage, bbox);subplot(2, 3, 5);imshow(croppedImageRGB);grid on;title('Cropped RGB Image', 'FontSize', fontSize);% Gray scale version of cropped image
croppedImageGray = imcrop(grayImage, bbox);subplot(2, 3, 6);imshow(croppedImageGray);grid on;title('Cropped Gray Scale Image', 'FontSize', fontSize);
Use max() on the distances from the centroid to the boundary pixels. Then use circshift to move that index to the beginning:
% Find out where the max distance is.
[maxDistance, indexOfMaxDistance] = max(distances);% Shift that index to be at index #1.
newDistances = circshift(distances, -(indexOfMaxDistance-1));Then you will have to subsample that to get indexes only at every 10 degrees. This means that for every boundary point, you have to compute its angle as well as its distances using atand2(). I hope you can figure out that part.
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