By using hough transform
How we can transform the first mage points to hough plane ??
Computer vision course
by using hough transformation find the exact C-u , c) line whrch the X Plane heas Two poin Co,1)C1.2) 5 ines how we can represent i 2 mdhow 2 1 2345 Point s ine s.
Solution
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); % 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
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By using hough transform How we can transform the first mage points to.docx
1. By using hough transform
How we can transform the first mage points to hough plane ??
Computer vision course
by using hough transformation find the exact C-u , c) line whrch the X Plane heas Two poin
Co,1)C1.2) 5 ines how we can represent i 2 mdhow 2 1 2345 Point s ine s.
Solution
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); %
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
![By using hough transform
How we can transform the first mage points to hough plane ??
Computer vision course
by using hough transformation find the exact C-u , c) line whrch the X Plane heas Two poin
Co,1)C1.2) 5 ines how we can represent i 2 mdhow 2 1 2345 Point s ine s.
Solution
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); %
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](https://image.slidesharecdn.com/byusinghoughtransformhowwecantransformthefirstmagepointsto-230204022349-bda2a84d/85/By-using-hough-transform-How-we-can-transform-the-first-mage-points-to-docx-1-320.jpg)
