
having difficulty in simple circle detection
3 visualizzazioni (ultimi 30 giorni)
Mostra commenti meno recenti
Abhilash Uniyal
il 11 Mag 2020
Commentato: Abhilash Uniyal
il 11 Mag 2020
Hi,
I am having difficulty finding a circle.
I already tried 'imfindcirles' , with different sensitivity but failed.
please help in this. i want to find the radius and center point of the dark blue circel (image attached).
Thanks in advance.
0 Commenti
Risposta accettata
Image Analyst
il 11 Mag 2020
Modificato: Image Analyst
il 11 Mag 2020
Use the Color Thresholder app on the apps tab of the tool ribbon. I'd use hsv color space. Then adjust the thresholds and Export the code into a new function m-file.
rgbImage = imread('Captur11.jpg');
subplot(2, 1, 1);
imshow(rgbImage);
[BW,maskedRGBImage] = createMask(rgbImage);
% Fill holes
BW = imfill(BW, 'holes');
% Take largest blob.
BW = bwareafilt(BW, 1);
subplot(2, 1, 2);
imshow(BW)
function [BW,maskedRGBImage] = createMask(RGB)
%createMask Threshold RGB image using auto-generated code from colorThresholder app.
% [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
% auto-generated code from the colorThresholder app. The colorspace and
% range for each channel of the colorspace were set within the app. The
% segmentation mask is returned in BW, and a composite of the mask and
% original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 11-May-2020
%------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.584;
channel1Max = 0.619;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.856;
channel2Max = 1.000;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.000;
channel3Max = 1.000;
% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
(I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
(I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image.
maskedRGBImage = RGB;
% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end

3 Commenti
Image Analyst
il 11 Mag 2020
Modificato: Image Analyst
il 11 Mag 2020
Try this:
props = regionprops(BW, 'Centroid', 'EquivDiameter');
radius = props.EquivDiameter / 2;
xCenter = props.Centroid(1);
yCenter = props.Centroid(2);
[r, g, b] = imsplit(rgbImage);
meanR = mean(r(BW))
meanG = mean(g(BW))
meanB = mean(b(BW))
Più risposte (0)
Vedere anche
Categorie
Scopri di più su Image Processing and Computer Vision in Help Center e File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!