Enclosing Boundary - for blobs
이전 댓글 표시
Hi all
Is it possible to get the boundary central more dense region - ignoring the blobs on the side
댓글 수: 6
DGM
2021년 7월 3일
You might want to describe the method you're currently using.
Image Analyst
2021년 7월 3일
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?
Conor O'Keeffe
2021년 7월 4일
Image Analyst
2021년 7월 4일
@Conor O'Keeffe, after seeing your original gray scale image, I think Matt's solution is the one you should use and Accept.
DGM
2021년 7월 4일
I think I'd agree with that.
Conor O'Keeffe
2021년 7월 4일
채택된 답변
추가 답변 (1개)
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)

카테고리
도움말 센터 및 File Exchange에서 Convert Image Type에 대해 자세히 알아보기
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!
