Cut An Image
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Hi All,
Is there a way by which we can separate an image like this?
I would like to get an output like below.
I tried morphological operation but i could not and I am not sure that it is a true way.
Thanks in advance.
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Chandra Kurniawan
2011년 12월 15일
clear; clc;
I = imread('tamp9f.png');
Icrop = imcrop(I);
bw = im2bw(Icrop);
imshow(bw); pause;
Ifill = imfill(bw,'holes');
imshow(Ifill); pause;
Iarea = bwareaopen(Ifill,10000);
imshow(Iarea); pause;
boundary = bwboundaries(Iarea);
b = boundary{1};
imshow(Ifill); hold on;
plot(b(:,2),b(:,1),'g','LineWidth',3);
The Result :
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Nour
2014년 12월 21일
yeah just got that the post is not effective, i've just post it again, and it is ok now.
Thanks in advance!
추가 답변 (1개)
Image Analyst
2011년 12월 15일
Here's one of my functions that you might be able to use. It accepts a binary image and returns the "N" largest blobs in the output image.
% Retain the "numberToKeep" biggest blobs in a binary image.
function keeperBlobsImage = RetainLargestBlobs(binaryImage, numberToKeep)
try
% Label each blob so can do calc on it
[labeledImage numberOfBlobs] = bwlabel(binaryImage, 8);
% Make sure we don't attempt to keep more blobs than actually exist.
if numberToKeep > numberOfBlobs
numberToKeep = numberOfBlobs;
end
% Make the area measurements.
blobMeasurements = regionprops(labeledImage, 'Area'); % Get the blob properties of 'Area'
allAreas = [blobMeasurements.Area];
% Get a list of the blobs that meet our criteria and we need to keep.
[sortedAreas sortedIndices] = sort(allAreas, 'descend');
keeperIndexes = sortedIndices(1 : numberToKeep);
% 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);
catch ME
errorMessage = sprintf('Error in function RetainLargestBlobs.\n\nError Message:\n%s', ME.message);
WarnUser(errorMessage);
end
return; % from RetainLargestBlobs
Once you have the largest blob you can try to smooth the boundaries using alpha shapes ( http://cgm.cs.mcgill.ca/~godfried/teaching/projects97/belair/alpha.html ) or morphological methods such as alternating sequential filters ( http://www.esiee.fr/~coupriem/Pdf/cb04.pdf )
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