function [rho,theta,houghSpace] = houghTransform(theImage,thetaSampleFrequency) %Define the hough space theImage = flipud(theImage); [width,height] = size(theImage); rhoLimit = norm([width height]); rho = (-rhoLimit:1:rhoLimit); theta = (0:thetaSampleFrequency:pi); numThetas = numel(theta); houghSpace = zeros(numel(rho),numThetas); %Find the "edge" pixels [xIndicies,yIndicies] = find(theImage); %Preallocate space for the accumulator array numEdgePixels = numel(xIndicies); accumulator = zeros(numEdgePixels,numThetas); %Preallocate cosine and sine calculations to increase speed. In %addition to precallculating sine and cosine we are also multiplying %them by the proper pixel weights such that the rows will be indexed by %the pixel number and the columns will be indexed by the thetas. %Example: cosine(3,:) is 2*cosine(0 to pi) % cosine(:,1) is (0 to width of image)*cosine(0) cosine = (0:width-1)'*cos(theta); %Matrix Outerproduct sine = (0:height-1)'*sin(theta); %Matrix Outerproduct accumulator((1:numEdgePixels),:) = cosine(xIndicies,:) + sine(yIndicies,:); %Scan over the thetas and bin the rhos for i = (1:numThetas) houghSpace(:,i) = hist(accumulator(:,i),rho); end pcolor(theta,rho,houghSpace); shading flat; title('Hough Transform'); xlabel('Theta (radians)'); ylabel('Rho (pixels)'); colormap('gray'); end
来源：http://stackoverflow.com/questions/9916253/hough-transform-in-matlab-without-using-hough-function
