MATLAB: How to reduce perimeter of Image in Matlab

erodeImage Processing ToolboxMATLAB

Hi,

I want to erode (Reduce the perimeter) of the below image by 7 pixels such that only the image within the red circle is kept.

I thought this could be done with imerode, but this also reduces the central pixels which I do not want!

Thank You 🙂

Best Answer

Try this:

se = strel('disk', 7, 0);
binaryImage = grayImage > 0; % Threshold.
mask = imerode(binaryImage, se);
grayImage(~mask) = 0;

Related Solutions

MATLAB: How to remove the boundary(only) of this image

It's very simple and is basically 3 or 4 steps. Basically threshold and fill the mask so you get a solid disk. Then shrink it a bit with imerode() to exclude the outer ring. Then everything outside that ring in your original image should be set to white. Here's a full demo.

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 gray scale demo image.
folder = pwd;
baseFileName = 'image11.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') 
% Threshold the image
binaryImage = grayImage < 128;
% Display the image.
subplot(2, 2, 2);
imshow(binaryImage, []);
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Fill the image
binaryImage = imfill(binaryImage, 'holes');
% Erode it a bit to come within the couter circle.
se = strel('disk', 5, 0); % Make round structuring element.
binaryImage = imerode(binaryImage, se);
% Display the image.
subplot(2, 2, 3);
imshow(binaryImage, []);
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% "Erase" outside the mask by setting the original image to white.
grayImage(~binaryImage) = 255; 
% Display the image.
subplot(2, 2, 4);
imshow(grayImage, []);
title('Final Gray Scale Image', 'FontSize', fontSize, 'Interpreter', 'None');

MATLAB: Threshold image after applying mask

I think imbinarize() and graythresh() work on 1-D images. So if you want to determine the a threshold only considering the gray levels of the gray ring and not considering the black background, extract the ring pixels into a list and pass them to graythresh():

ringPixels = originalImage(originalImage > theThreshold); % No black pixels here
newThreshold = graythresh(ringPixels);

Since you've already masked the image by doing something like

maskedImage = originalImage; % Initialize
maskedImage(mask) = 0; % Erase background.

you could also do the first line like this

ringPixels = maskedImage(maskedImage > 0);

and then call graythresh();

Best Answer

Related Solutions

MATLAB: How to remove the boundary(only) of this image

MATLAB: Threshold image after applying mask

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