Registering an Image Using Normalized Cross-Correlation
This example shows how to find a template image within a larger image. Sometimes one image is a subset of another. Normalized cross-correlation can be used to determine how to register or align the images by translating one of them.
Step 1: Read Image
onion = imread("onion.png"); peppers = imread("peppers.png"); imshow(onion)
Step 2: Choose Subregions of Each Image
It is important to choose regions that are similar. The image
sub_onion will be the template, and must be smaller than the image
sub_peppers. You can get these subregions using either the non-interactive script below or the interactive script.
% non-interactively rect_onion = [111 33 65 58]; rect_peppers = [163 47 143 151]; sub_onion = imcrop(onion,rect_onion); sub_peppers = imcrop(peppers,rect_peppers); % OR % interactively %[sub_onion,rect_onion] = imcrop(onion); % choose the pepper below the onion %[sub_peppers,rect_peppers] = imcrop(peppers); % choose the whole onion % display sub images imshow(sub_onion)
Step 3: Do Normalized Cross-Correlation and Find Coordinates of Peak
Calculate the normalized cross-correlation and display it as a surface plot. The peak of the cross-correlation matrix occurs where the subimages are best correlated.
normxcorr2 only works on grayscale images, so we pass it the red plane of each subimage.
c = normxcorr2(sub_onion(:,:,1),sub_peppers(:,:,1)); figure surf(c) shading flat
Step 4: Find the Total Offset Between the Images
The total offset or translation between images depends on the location of the peak in the cross-correlation matrix, and on the size and position of the subimages.
% offset found by correlation [max_c,imax] = max(abs(c(:))); [ypeak,xpeak] = ind2sub(size(c),imax(1)); corr_offset = [(xpeak-size(sub_onion,2)) (ypeak-size(sub_onion,1))]; % relative offset of position of subimages rect_offset = [(rect_peppers(1)-rect_onion(1)) (rect_peppers(2)-rect_onion(2))]; % total offset offset = corr_offset + rect_offset; xoffset = offset(1); yoffset = offset(2);
Step 5: See if Onion Image was Extracted from Peppers Image
Figure out where
onion falls inside of
xbegin = round(xoffset + 1); xend = round(xoffset + size(onion,2)); ybegin = round(yoffset + 1); yend = round(yoffset + size(onion,1)); % extract region from peppers and compare to onion extracted_onion = peppers(ybegin:yend,xbegin:xend,:); if isequal(onion,extracted_onion) disp("onion.png was extracted from peppers.png") end
onion.png was extracted from peppers.png
Step 6: Pad Onion Image to Size of Peppers Image
onion image to overlay on
peppers, using the offset determined above.
recovered_onion = uint8(zeros(size(peppers))); recovered_onion(ybegin:yend,xbegin:xend,:) = onion; imshow(recovered_onion)
Step 7: Use Alpha Blending to Show Images Together
Display one plane of the
peppers image with the
recovered_onion image using alpha blending.