% Demonstration of feature matching via simple correlation, and then using% RANSAC to estimate the fundamental matrix and at the same time identify% (mostly) inlying matches%% Usage:  testfund              - Demonstrates fundamental matrix calculation%                                 on two default images%         testfund(im1,im2)     - Computes fundamental matrix on two supplied images%% Edit code as necessary to tweak parameters% Copyright (c) 2004-2005 Peter Kovesi% School of Computer Science & Software Engineering% The University of Western Australia% http://www.csse.uwa.edu.au/% % Permission is hereby granted, free of charge, to any person obtaining a copy% of this software and associated documentation files (the "Software"), to deal% in the Software without restriction, subject to the following conditions:% % The above copyright notice and this permission notice shall be included in % all copies or substantial portions of the Software.%% The Software is provided "as is", without warranty of any kind.% February 2004% August   2005 Octave compatibilityfunction testfund(im1,im2)        if nargin == 0	im1 = imread('im02.jpg');	im2 = imread('im03.jpg');    end    v = version; Octave=v(1)<'5';  % Crude Octave test            thresh = 500;   % Harris corner threshold    nonmaxrad = 3;  % Non-maximal suppression radius    dmax = 50;      % Maximum search distance for matching    w = 11;         % Window size for correlation matching        % Find Harris corners in image1 and image2    [cim1, r1, c1] = harris(im1, 1, thresh, 3);    show(im1,1), hold on, plot(c1,r1,'r+');    [cim2, r2, c2] = harris(im2, 1, thresh, 3);    show(im2,2), hold on, plot(c2,r2,'r+');    drawnow    correlation = 1;  % Change this between 1 or 0 to switch between the two                      % matching functions below        if correlation  % Use normalised correlation matching	[m1,m2] = matchbycorrelation(im1, [r1';c1'], im2, [r2';c2'], w, dmax);	    else            % Use monogenic phase matching	nscale = 1;	minWaveLength = 10;	mult = 4;	sigmaOnf = .2;	[m1,m2] = matchbymonogenicphase(im1, [r1';c1'], im2, [r2';c2'], w, dmax,...					nscale, minWaveLength, mult, sigmaOnf);    end            % Display putative matches    show(im1,3), set(3,'name','Putative matches')    if Octave, figure(1); title('Putative matches'), axis('equal'), end            for n = 1:length(m1);	line([m1(2,n) m2(2,n)], [m1(1,n) m2(1,n)])    end    % Assemble homogeneous feature coordinates for fitting of the    % fundamental matrix, note that [x,y] corresponds to [col, row]    x1 = [m1(2,:); m1(1,:); ones(1,length(m1))];    x2 = [m2(2,:); m2(1,:); ones(1,length(m1))];            t = .002;  % Distance threshold for deciding outliers        % Change the commenting on the lines below to switch between the use    % of 7 or 8 point fundamental matrix solutions, or affine fundamental    % matrix solution.%   [F, inliers] = ransacfitfundmatrix7(x1, x2, t, 1);        [F, inliers] = ransacfitfundmatrix(x1, x2, t, 1);%   [F, inliers] = ransacfitaffinefund(x1, x2, t, 1);        fprintf('Number of inliers was %d (%d%%) \n', ...	    length(inliers),round(100*length(inliers)/length(m1)))    fprintf('Number of putative matches was %d \n', length(m1))                % Display both images overlayed with inlying matched feature points        if Octave	figure(4); title('Inlying matches'), axis('equal'),     else        show(im1,4), set(4,'name','Inlying matches'), hold on    end            plot(m1(2,inliers),m1(1,inliers),'r+');    plot(m2(2,inliers),m2(1,inliers),'g+');        for n = inliers	line([m1(2,n) m2(2,n)], [m1(1,n) m2(1,n)],'color',[0 0 1])    end    if Octave, return, end        response = input('Step through each epipolar line [y/n]?\n','s');    if response == 'n'	return    end            % Step through each matched pair of points and display the    % corresponding epipolar lines on the two images.        l2 = F*x1;    % Epipolar lines in image2    l1 = F'*x2;   % Epipolar lines in image1        % Solve for epipoles    [U,D,V] = svd(F);    e1 = hnormalise(V(:,3));    e2 = hnormalise(U(:,3));     for n = inliers	figure(1), clf, imshow(im1), hold on, plot(x1(1,n),x1(2,n),'r+');	hline(l1(:,n)); plot(e1(1), e1(2), 'g*');	figure(2), clf, imshow(im2), hold on, plot(x2(1,n),x2(2,n),'r+');	hline(l2(:,n)); plot(e2(1), e2(2), 'g*');	fprintf('hit any key to see next point\r'); pause    end    fprintf('                                         \n');