Enclosing Boundary - for blobs

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Conor O'Keeffe
Conor O'Keeffe 2021-7-3
评论： Conor O'Keeffe 2021-7-4
Hi all
Is it possible to get the boundary central more dense region - ignoring the blobs on the side
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DGM
DGM 2021-7-4
I think I'd agree with that.
Conor O'Keeffe
Conor O'Keeffe 2021-7-4
Yes thats great, thank you all for the help. Seems to be matching to the greyscale image (attached)

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Matt J
Matt J 2021-7-3
编辑：Matt J 2021-7-3
Ran in:
Perhaps as follows,
BW0=load('Image.mat').BW;
BW= imclose(BW0,strel('disk',3));
BW = imfill( BW ,'holes') ;
BW=bwareafilt( BW,1);
boundary=fliplr( cell2mat( bwboundaries( BW ) ) );
imshow(insertMarker(double(BW0),boundary,'o','Size',1,'Color','m'));

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DGM
DGM 2021-7-3
编辑：DGM 2021-7-4
I'll throw this out there. I'm assuming that the goal here is density-dependent (linear) mask constriction. On that assumption, I'm avoiding erosion and using an averaging filter and thresholding. It works, but it would likely require adjustment, considering I don't know what the particular limits are or what other images will look like.
% parameters
frad = 15;
masklevel = 0.1;
outlevel = 0.18;
% flattened, binarized image
inpict = rgb2gray(imread('capture.jpg'))>128;
% if you want to filter by local density, maybe use an avg filter
wpict = imfilter(double(inpict),fspecial('disk',frad));
% first pass to get rid of stray exterior points
mask = double(bwareafilt(wpict>masklevel,1));
wpict = wpict.*mask;
% second pass to tighten group following density
wpict = wpict>outlevel;
% as opposed to erosion which follows envelope
%wpict = imerode(wpict,strel('disk',10));
% for viewing, i'm just going to slap together a weighted mean
% you can use whatever you want. wpict is just a binary mask like any other.
k = 0.3;
comp = inpict*k + wpict*(1-k);
imshow(comp)

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