MATLAB: Eliminating Groups of Connected Pixels.

bwareaopenImage Processing Toolbox

I would like to be able to look at the matrices of an image and convert certain connected pixel groups from 1’s to 0’s. I would like to be able look at each individual rows and columns and convert groups or individual pixel that are smaller than a defined amount of pixels. I have used the bwareaopen function to eliminate pixel groups that are smaller than a defined amount. But I cannot determine how to use this concept for individual rows or columns.

For example, I would like to eliminate the square in the first image below. . .

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Best Answer

First of all, you shouldn't use highly compressed jepg images for image analysis or else you get bad artifacts like you're seeing.

The "square" is the outermost object and will have label 1. So label everything and remove it. Something like this (untested off the top of my head);

[labeledImage, numberOfRegions] = bwlabel(binaryImage);
% Binarize the labeled image to get back to a binary image again.
binaryImage = labeledImage > 1; % Keep all except region #1.

Related Solutions

MATLAB: Number of Object in binary image

Try this:

bw = imread('bw.png');
if ndims(bw) > 1
	bw = bw(:,:,1);
end
% Threshold
bw = bw > 128;
subplot(1, 2, 1);
imshow(bw, []);
% Fill holes
bw = imfill(bw, 'holes');
% Get areas
props = regionprops(bw, 'Area');
sortedAreas = sort([props.Area], 'descend')
% Looks like we need to throw away any blobs less than 1000 pixels or so
bw = bwareaopen(bw, 1000);
subplot(1, 2, 2);
imshow(bw);
% Count the blobs
[labeledImage, numBlobs] = bwlabel(bw);
fprintf('Found %d shapes.\n', numBlobs);

MATLAB: How to dilate only a portion of an image

This can be implemented using various Image Processing Toolbox functions. The attached example code implements the following algorithm to achive the desired result:

1. Label components using the BWLABEL function. The BWLABEL function returns a matrix 'L' of the same size as the image. Note each component is labeled with a different value and the label throughout one component is the same.

2. Now get a histogram of 'L' to get a count of the number of pixels in each component using the HIST function.

3. Get the label values for which the count is less than 5, that is, the number of pixels in that component is less than 5.

4. Iterate though all of the small components to save their row and column values in cell arrays 'M' and 'N'.

5. Modify the original image to set the small component intensity values to be 0 (black).

6. Perform a dilation operation on this image using the IMDILATE function using a rectangular structural element by STREL function.

7. Iterate through the small components to set their pixel values in this new image to be 1 (white).

Another way to implement this functionality is using the BWAREAOPEN function which morphologically open binary image (remove small objects):

I = imread('rice.png');
level = graythresh(I);
BW = im2bw(I,level);    % Binary Image
figure(1)
imshow(BW);
title('Original Image');
% Remove all components which have fewer than 5 pixels
im1 = bwareaopen(BW,5);
im2 = imdilate(im1, strel('square',3));
% Perform logical oring operation between the dilated and original image to get back the % small components
outputIm = im2 | BW;
figure(2)
imshow(outputIm);
title('Final Image')

Best Answer

Related Solutions

MATLAB: Number of Object in binary image

MATLAB: How to dilate only a portion of an image

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