Enclosing Boundary - for blobs

Hi all
Is it possible to get the boundary central more dense region - ignoring the blobs on the side

6 Comments

You might want to describe the method you're currently using.
What does this thing represent? What is the real world object you images to get this? Is the real object known to be a rectangle or cylinder, with straight sides, or does it have ragged sides?
Sorry yeah, the original image is attaced. I want to get the outline of the metal strut.
Basically getting to this point by thresholding.
Its an old image Im going back to so wasent thinking about getting a good contrast.
@Conor O'Keeffe, after seeing your original gray scale image, I think Matt's solution is the one you should use and Accept.
I think I'd agree with that.
Yes thats great, thank you all for the help. Seems to be matching to the greyscale image (attached)

Sign in to comment.

 Accepted Answer

Matt J
Matt J on 3 Jul 2021
Edited: Matt J on 3 Jul 2021
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'));

More Answers (1)

DGM
DGM on 3 Jul 2021
Edited: DGM on 4 Jul 2021
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)

Categories

Find more on Convert Image Type in Help Center and File Exchange

Community Treasure Hunt

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

Start Hunting!