Note, I used Computer Vision Toolbox below.
Capture_img = imread('Capture.jpg');
Picture1_img = imread('Picture1.png');
imshow(Capture_img)
imshow(Picture1_img)
size(Picture1_img)
size(Capture_img)
Using the Registration Estimator app to make sure images are co-registered:
[NewPicture1_img] = registerImages(Picture1_img,Capture_img)
imshow(NewPicture1_img.RegisteredImage)
Picture1_img=NewPicture1_img.RegisteredImage;
imshow(Picture1_img(:,:,1))
imshow(Picture1_img(:,:,1)>225&Picture1_img(:,:,2)==0)% When red slice intensity values are greater than 225 and green slice intensity values are equal to 0.
% Convert logical matrix into 8-bit image then multiply by Capture_img
imshow(Capture_img.*uint8(Picture1_img(:,:,1)>225&Picture1_img(:,:,2)==0))
function [MOVINGREG] = registerImages(MOVING,FIXED)
%registerImages Register grayscale images using auto-generated code from Registration Estimator app.
% [MOVINGREG] = registerImages(MOVING,FIXED) Register grayscale images
% MOVING and FIXED using auto-generated code from the Registration
% Estimator app. The values for all registration parameters were set
% interactively in the app and result in the registered image stored in the
% structure array MOVINGREG.
% Auto-generated by registrationEstimator app on 09-Jan-2023
%-----------------------------------------------------------
% Feature-based techniques require license to Computer Vision Toolbox
checkLicense()
% Convert RGB images to grayscale
FIXED = im2gray(FIXED);
MOVINGRGB = MOVING;
MOVING = im2gray(MOVING);
% Default spatial referencing objects
fixedRefObj = imref2d(size(FIXED));
movingRefObj = imref2d(size(MOVING));
% Detect SURF features
fixedPoints = detectSURFFeatures(FIXED,'MetricThreshold',750.000000,'NumOctaves',3,'NumScaleLevels',5);
movingPoints = detectSURFFeatures(MOVING,'MetricThreshold',750.000000,'NumOctaves',3,'NumScaleLevels',5);
% Extract features
[fixedFeatures,fixedValidPoints] = extractFeatures(FIXED,fixedPoints,'Upright',false);
[movingFeatures,movingValidPoints] = extractFeatures(MOVING,movingPoints,'Upright',false);
% Match features
indexPairs = matchFeatures(fixedFeatures,movingFeatures,'MatchThreshold',50.000000,'MaxRatio',0.500000);
fixedMatchedPoints = fixedValidPoints(indexPairs(:,1));
movingMatchedPoints = movingValidPoints(indexPairs(:,2));
MOVINGREG.FixedMatchedFeatures = fixedMatchedPoints;
MOVINGREG.MovingMatchedFeatures = movingMatchedPoints;
% Apply transformation - Results may not be identical between runs because of the randomized nature of the algorithm
tform = estimateGeometricTransform2D(movingMatchedPoints,fixedMatchedPoints,'projective');
MOVINGREG.Transformation = tform;
MOVINGREG.RegisteredImage = imwarp(MOVINGRGB, movingRefObj, tform, 'OutputView', fixedRefObj, 'SmoothEdges', true);
% Store spatial referencing object
MOVINGREG.SpatialRefObj = fixedRefObj;
end
function checkLicense()
% Check for license to Computer Vision Toolbox
CVTStatus = license('test','Video_and_Image_Blockset');
if ~CVTStatus
error(message('images:imageRegistration:CVTRequired'));
end
end
