removing objects which have area greater and lesser than some threshold areas and extracting only the objects which have the area in between

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Hi, I am doing a project on nighttime vehicle detection. I have extracted bright objects from the input traffic image.I have to remove smaller objects(noise) and larger objects(reflections) when compared to vehicle headlight objects. I have removed small objects using "sterl" function. How can i remove larger objects? Please help me in extracting based on the area of these objects. I have to extract only the in between area objects.
Thank you sir.
  4 Comments
Amrutha c
Amrutha c on 25 Jul 2019
how to extract the bright objects(segmentation using adaptive thresholding) like head light during night time driving conditions using matlab code
Image Analyst
Image Analyst on 25 Jul 2019
Amrutha, start your own question, and attach your own image. You can threshold to find the brightest things. See my Image Segmentation Tutorial in My File Exchange

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Accepted Answer

Teja Muppirala
Teja Muppirala on 21 Aug 2012
Given some image, for example (just to make a random image):
I = conv2(randn(500),ones(10)) > 10;
imshow(I);
To keep only objects between, say, 30 pixels and 50 pixels in area, you can use the BWAREAOPEN command, like this:
LB = 30;
UB = 50;
Iout = xor(bwareaopen(I,LB), bwareaopen(I,UB));
figure, imshow(Iout);
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More Answers (2)

Image Analyst
Image Analyst on 21 Aug 2012
Edited: Image Analyst on 21 Aug 2012
You can use the ismember() function. Look at this snippet adapted from my BlobsDemo image segmentation tutorial http://www.mathworks.com/matlabcentral/fileexchange/?term=authorid%3A31862. Don't worry - it's only a few lines. It just looks long because of all the comments. Read the comments. They are quite informative and instructive.
% 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 area between 1500 and 20000 pixels.
allBlobAreas = [blobMeasurements.Area];
% Get a list of the blobs that meet our criteria and we need to keep.
allowableAreaIndexes = (allBlobAreas > 1500) & (allBlobAreas < 20000);
% That's a logical map of what indexed acceptable blobs are at.
% Like 0 0 1 0 1 0 0 1 1 0 0 1 0 1 0 0 1
% We need the actual index, like blobs #3, 5, 8, 9, 12, 14, and 17
% (to use the above logical array as an example).
keeperIndexes = find(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.
keeperBlobsImage = ismember(labeledImage, keeperIndexes);
% Re-label with only the keeper blobs kept.
newLabeledImage = 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.
imshow(newLabeledImage , []);
title('"Keeper" blobs');

Jürgen
Jürgen on 21 Aug 2012
Hi,
to get properties from areas of blob in the image You have to do labeling first or transfrom to BW images then you can use STATS = regionprops(BW, properties) which give you all kind of information on the labeled objects. Area is one of them. regards,Jürgen
  4 Comments
Natalia Demidova
Natalia Demidova on 28 Jul 2021
After extracting said largest blob (after initially using regionprops, specifically), how would you then remove it (i.e. correspond with the actual blob location?)
Image Analyst
Image Analyst on 28 Jul 2021
largestBlob = bwareafilt(binaryImage, 1);
allExceptLargest = binaryImage & (~largestBlob); % Erase largest from the original

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