Create binary image using label matrix for corresponding cluster

3 次查看（过去 30 天）
tan yuki
tan yuki 2016-1-30
编辑： Image Analyst 2016-1-30
I am doing a project to segment a cell image into a few region using k-means. I have found a useful example using adaptive k-means without the need to specify the cluster number and the link is as below.
http://www.mathworks.com/matlabcentral/fileexchange/45057-adaptive-kmeans-clustering-for-color-and-gray-image
However i face some problem to display the clustered image as the segmented image from original image. I was advice to use label matrix as a mask to create a binary image for corresponding label(clustered image) and then multiply the mask to original image in order to obtain the segmented image.
Any suggestion or advice how to do this? Thanks

请先登录，再回答此问题。

回答（2 个）

Walter Roberson
Walter Roberson 2016-1-30
Presuming that the results of calling that function are in the variable LB
num_blob = max(LB(:));
for K = 1 : numblob
ax = subplot(1, num_blob, K);
mask = repmat(LB == K, 1, 1, 3);
masked_image = YourRGBImage .* mask;
image(ax, masked_image);
axis(ax, 'image');
title(ax, sprintf('blob %#d', K));
end
Image Analyst
Image Analyst 2016-1-30
编辑：Image Analyst 2016-1-30
Assuming you have a labeled image where every color that you care about has a label of an integer 1 or more, and everything that you don't care about has a value of 0, you can mask the image like this:
mask = labeledImage > 0; % Get stuff we care about.
% Mask the image using bsxfun() function
maskedRgbImage = bsxfun(@times, rgbImage, cast(mask, 'like', rgbImage));

类别

在 Help Center 和 File Exchange 中查找有关 Image Segmentation 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by