SIFT+RANSAC

% [matchLoc1 matchLoc2] = siftMatch(img1, img2) % % This function reads two images, finds their SIFT features, and % displays lines connecting the matched keypoints. A match is accepted % only if its distance is less than distRatio times the distance to the % second closest match. % It returns the matched points of both images, matchLoc1 = [x1,y1;x2,y2;...] % % Example: match('scene.pgm','book.pgm'); function [matchLoc1 matchLoc2] = siftMatch(img1, img2) % load matchdata % load img1data % load img2data %{, % Find SIFT keypoints for each image [des1, loc1] = sift(img1); [des2, loc2] = sift(img2); % save img1data des1 loc1 % save img2data des2 loc2 % For efficiency in Matlab, it is cheaper to compute dot products between % unit vectors rather than Euclidean distances. Note that the ratio of % angles (acos of dot products of unit vectors) is a close approximation % to the ratio of Euclidean distances for small angles. % % distRatio: Only keep matches in which the ratio of vector angles from the % nearest to second nearest neighbor is less than distRatio. distRatio = 0.6; % For each descriptor in the first image, select its match to second image. des2t = des2'; % Precompute matrix transpose matchTable = zeros(1,size(des1,1)); for i = 1 : size(des1,1) dotprods = des1(i,:) * des2t; % Computes vector of dot products [vals,indx] = sort(acos(dotprods)); % Take inverse cosine and sort results % Check if nearest neighbor has angle less than distRatio times 2nd. if (vals(1) < distRatio * vals(2)) matchTable(i) = indx(1); else matchTable(i) = 0; end end % save matchdata matchTable %} % Create a new image showing the two images side by side. % img3 = appendimages(img1,img2); % Show a figure with lines joining the accepted matches. % figure('Position', [100 100 size(img3,2) size(img3,1)]); % colormap('gray'); % imagesc(img3); % hold on; % cols1 = size(img1,2); % for i = 1: size(des1,1) % if (matchTable(i) > 0) % line([loc1(i,2) loc2(matchTable(i),2)+cols1], ... % [loc1(i,1) loc2(matchTable(i),1)], 'Color', 'c'); % end % end % hold off; % num = sum(matchTable > 0); % fprintf('Found %d matches.\n', num); idx1 = find(matchTable); idx2 = matchTable(idx1); x1 = loc1(idx1,2); x2 = loc2(idx2,2); y1 = loc1(idx1,1); y2 = loc2(idx2,1); matchLoc1 = [x1,y1]; matchLoc2 = [x2,y2]; end