MATLAB: Removal Of objects from binary image.

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Hello, actually I am new to matlab and want to know how to remove some objects from a binary image based upon area. Such that when a particular threshold is set the components of image having area above threshold is removed. Like removing a large vessel of eye and not removing small ones. Is there any function??? Please provide assistance!

Best Answer

once you have got the binary image,you can do the following:

 outputImage = xor(BW , bwareaopen(BW , threshArea)); 
                 % BW being the binary image
                 % it will discard objects with area greater then threshArea
 imshow(outputImage)

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MATLAB: Centroid of thin-edged (One Pixel thickness) connected blobs

regionprops(bwconncomp((imfill(A,'holes')-A),4),'centroid')

1) Fill the holes/"blobs" in the image.

2) Subtract the boundaries from the filled image to obtain 2 disconnected blobs (4 way connectivity due to pixelization).

3) Find individual blobs.

4) Find their centroid.

MATLAB: How to extract objects from an image after i have measured properties through regionprops

See my image segmentation tutorial - it goes over all of that. http://www.mathworks.com/matlabcentral/fileexchange/25157-image-segmentation-tutorial

Here's the relevant snippet. Change the filter parameters to be eccentricity and aspect ratio and you're all set.

% Now I'll demonstrate how to select certain blobs based using the ismember() function.
% Let's say that we wanted to find only those blobs
% with an intensity between 150 and 220 and an area less than 2000 pixels.
% This would give us the three brightest dimes (the smaller coin type).
allBlobIntensities = [blobMeasurements.MeanIntensity];
allBlobAreas = [blobMeasurements.Area];
% Get a list of the blobs that meet our criteria and we need to keep.
% These will be logical indices - lists of true or false depending on whether the feature meets the criteria or not.
% for example [1, 0, 0, 1, 1, 0, 1, .....].  Elements 1, 4, 5, 7, ... are true, others are false.
allowableIntensityIndexes = (allBlobIntensities > 150) & (allBlobIntensities < 220);
allowableAreaIndexes = allBlobAreas < 2000; % Take the small objects.
% Now let's get actual indexes, rather than logical indexes, of the  features that meet the criteria.
% for example [1, 4, 5, 7, .....] to continue using the example from above.
keeperIndexes = find(allowableIntensityIndexes & allowableAreaIndexes);
% Extract only those blobs that meet our criteria, and
% eliminate those blobs that don't meet our criteria.
% Note how we use ismember() to do this.  Result will be an image - the same as labeledImage but with only the blobs listed in keeperIndexes in it.
keeperBlobsImage = ismember(labeledImage, keeperIndexes);
% Re-label with only the keeper blobs kept.
labeledDimeImage = bwlabel(keeperBlobsImage, 8);     % Label each blob so we can make measurements of it
% Now we're done.  We have a labeled image of blobs that meet our specified criteria.

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Related Solutions

MATLAB: Centroid of thin-edged (One Pixel thickness) connected blobs

MATLAB: How to extract objects from an image after i have measured properties through regionprops

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