MATLAB: How to measure the shortest distance from a point to the edge

binarycolordistanceimage analysisimage segmentation

Hi All,

Can somebody help me how to measure the shortest length ( Perpendicular length) from the dots indicated inside black rectangle to the edge of the black portion on both sides in the following image ?? also, how to measure the shortest length between the points indicated in blue color??

https://picasaweb.google.com/116243239493929305987/January42012#5693806876116607234

Best Answer

I see the black band, and I see scattered white dots. I do not see any blue points?

The shortest distance from a point (x,y) to the edge of the black is

min([x, width-x, y, height-y])

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MATLAB: Image Analysis: measuring cusping and roughness

Here's how I would approach it:

% Read the image and convert to BW mask of peaks
I_orig = imread('cusp_micro.jpg');
I = rgb2gray(I_orig);
BW_peaks = im2bw(I);
% How far is every non-peak pixel from its nearest peak?
distFromPeaks = bwdist(BW_peaks);
% Let's only choose pixels further from a peak than any of its neighbours
maxDistsMask = imregionalmax(distFromPeaks);
[trI,trJ] = find(maxDistsMask);
trVals = I(maxDistsMask);
tr2pkDists = distFromPeaks(maxDistsMask);
% Now loop over each trough and find the image intensity of its nearest
% peak (add 5 pixels padding so we choose the max from a few nearby peaks)
pkInds = find(BW_peaks);
[pkI,pkJ] = ind2sub(size(BW_peaks),pkInds);
trPartnerPkVals = zeros(size(trI));
for i = 1:length(trI)
    tr2allPkDists = sqrt((pkI-trI(i)).^2 + (pkJ-trJ(i)).^2);
    withinRangeMask = tr2allPkDists < (tr2pkDists(i) + 5);
    trPartnerPkVals(i) = max(I(pkInds(withinRangeMask)));
end
% Display what we've got:
I_norm = double(I)/double(max(I(:)));
figure, imshow(cat(3,I_norm,max(BW_peaks, I_norm),I_norm)), hold on
plot(trJ,trI,'m.')
% Now if we look at all of the maxdists in the image, how far away from
% peaks are they?
figure, plot(sort(tr2pkDists)), title 'Distribution of cusp spacing'
figure, plot(sort(trPartnerPkVals - double(I(maxDistsMask))))
title 'Distribution of roughness'

So the largest trough2pk distance (or cusp spacing) is around 40 pixels. Notice of course that there are a range of pk2trough values depending on where you look in the image, likewise measures of roughness. You may need a scheme to select maximum cusp spacing or roughness within an X-pixel radius of an area you're interested in, or something similar.

Thanks, Sven.

MATLAB: Cut an image based on pixel size

You can cut the blob up using morphological operations, as shown below.

A point on terminology: all pixels are the same size (in a conventionally sampled image anyway). The blobs are to be separated based on the width of any "necks" that they have.

The width of the necks in the image as downloaded is much less than the 200 pixels you mention in your example, but maybe your images are actually much larger. To adjust my code, you would change the value of the variable cutsize.

% image downloaded and stored as imorig
imbin = imorig(:,:,1) > max(imorig(:))/2;  % binarise
imclean = ~bwareaopen(imbin, 10);  % remove dots just inside the edge, and invert
cutsize = 5;   % half the thickness of the thickest neck to cut
ime = imerode(imclean, strel('disk',cutsize));  % cut necks
imthick = bwmorph(ime, 'thicken', cutsize);   % grow blobs, but don't join up
imsplit = imbin | ~imthick;  % split original image

Best Answer

Related Solutions

MATLAB: Image Analysis: measuring cusping and roughness

MATLAB: Cut an image based on pixel size

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