Effacer les filtres
Effacer les filtres

How can find connected region in RGB images?

1 vue (au cours des 30 derniers jours)
ali Jalil
ali Jalil le 13 Avr 2016
I have RGB, and i want to find connected regions in it?

Réponses (2)

DGM le 11 Avr 2024
This answer demonstrates how to generate a mask by box (range) or ellipsoid (distance) matching in RGB given a target color tuple.
I'm assuming the goal is to do something similar to grayconnected(), so the given example can be further expanded to include sampling from the image and selection of the region local to the sample point.
% inputs
inpict = imread('rainbow.png'); % uint8
tol = [0.2 0.3 0.3]; % pick some tolerance per axis
picklocation = [20 100]; % where to sample the color [x y]
sampleradius = 2.5; % for sample averaging (set to 0 to disable)
% show the image and mark the location
imshow(inpict); hold on
% prepare inputs
inpict = im2double(inpict); % put the image in a consistent scale
tol = permute(tol,[1 3 2]); % reorient tuple along page axis
% sample the image
fk = fspecial('disk',max(sampleradius,0.5));
r = ceil(sampleradius-0.5); % calculated window radius
xw = picklocation(1) + r + (-r:r); % (sample offset) + (padding offset) + (window indices)
yw = picklocation(2) + r + (-r:r);
padded = padarray(inpict,[r r],'symmetric','both');
pickedcolor = sum(fk.*padded(yw,xw,:),1:2); % sample average
% these are global color selections
% perform box (range) selection in RGB
boxmask = all(abs(inpict-pickedcolor) <= tol,3);
% perform ellipsoid (euclidean distance) selection in RGB
distmask = sum(((inpict-pickedcolor)./tol).^2,3) <= 1;
% restrict the selection to the local blob (magic wand behavior)
conn = 4; % connectivity
boxmasklocal = bwselect(boxmask,picklocation(1),picklocation(2),conn);
distmasklocal = bwselect(distmask,picklocation(1),picklocation(2),conn);

Image Analyst
Image Analyst le 12 Avr 2024
It's a generic, general purpose demo of how to threshold an image to find blobs, and then measure things about the blobs, and extract certain blobs based on their areas or diameters.
If you have any more questions, then attach your data and code to read it in with the paperclip icon after you read this:
Or you can look up the tag "color segmentation". It's been discussed hundreds of times.

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