Scale and Rotation invariant Template Matching
I think that you can solve you problem in a much easier way. Considering that you are dealing with blueprints, you should not worry about edge connectivity, noise, and many other things that SIFT and SURF were built to accommodate for. Your template is a hollow shape with specific edge shapes.

Thus, My recommendation is:


Walk around the perimeter and find a profile of distances of the edges around the center of the template. This is the radial profile of the template. Divide by largest distance, to be scale invariant. Rotate the vector so that the smallest distance is the first, to be rotation invariant. (If your template has no dominant distance, you can change step 2 later)





Find blobs in the image. Compute the radial profile described at part (1), and compare the two vectors by normalized correlation. If your template has no dominant distance, correlation becomes normalized cross-correlation, and selecting maximum). Those who pass some threshold are considered matches.


Here is some Matlab code for you to start with - I wrote the part that finds distance profile for a specific blob and calculated it for the template:

function Doors
    im = imread('http://i.stack.imgur.com/Tf8EV.png');
    im = im(:,:,1);
    template = imread('http://i.stack.imgur.com/PlP4i.png');
    template = template(:,:,1);

    blobs = regionprops(template&gt;0,'Area','Image');
    largestBlob = GetLargestBlob(blobs);
    [prof,edgeImage] = GetBlobRadialProfile(largestBlob);

    figure;
    subplot(1,2,1);plot(prof); title('Radial profile')
    subplot(1,2,2);imshow(edgeImage); title('Template');

end

function [prof,edgeImage] = GetBlobRadialProfile(blob)
    paddedImage = padarray( blob.Image,[8 8]);
    erodedImage = imerode(paddedImage,strel('disk',1));
    edgeImage = xor(erodedImage,paddedImage);

    c = regionprops(paddedImage,'Centroid');
    cx  = c.Centroid(1);
    cy  = c.Centroid(2);

    [y,x] = find(edgeImage);
    rad = (x(:)-cx).^2 + (y(:)-cy).^2;
    [~,minIndex] = min(rad);
    contour = bwtraceboundary(edgeImage, [y(minIndex), x(minIndex)],'N');
    prof = (contour(:,2)-cx).^2 + (contour(:,1)-cy).^2;
    prof = prof./max(prof);
end

function largestBlob = GetLargestBlob(blobs)    
    area = [blobs.Area];
    [~,index] = max(area);
    largestBlob = blobs(index);
end