MATLAB: Explaination about code line detection

digital image processingimage processingmatlab r2010awindows 7

hello… can everyone explain to me about codes below… thanks alot

 theta = -90:89;
 [R,xp] = radon(binaryImage,theta);
 [R1,r_max] = max(R); 
 theta_max = 90;
 while(theta_max > 50 || theta_max<-50)
    [R2,theta_max] = max(R1); 
    R1(theta_max) = 0; 
    theta_max = theta_max - 91;

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doc radon

Radon

Radon transform Syntax

R = radon(I, theta) [R,xp] = radon(...)

Description

R = radon(I, theta) returns the Radon transform R of the intensity image I for the angle theta degrees.

The Radon transform is the projection of the image intensity along a radial line oriented at a specific angle. If theta is a scalar, R is a column vector containing the Radon transform for theta degrees. If theta is a vector, R is a matrix in which each column is the Radon transform for one of the angles in theta. If you omit theta, it defaults to 0:179.

[R,xp] = radon(...) returns a vector xp containing the radial coordinates corresponding to each row of R.

The radial coordinates returned in xp are the values along the x'-axis, which is oriented at theta degrees counterclockwise from the x-axis. The origin of both axes is the center pixel of the image, which is defined as floor((size(I)+1)/2)

For example, in a 20-by-30 image, the center pixel is (10,15

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To apply PCA to an image, see this link: http://www.mathworks.com/matlabcentral/answers/167938#answer_163231 I don't think it will work, though you can try. Make sure you pass it the location of the black pixels, not the image gray levels.

I'd probably use a radon transform. See my attached demo where I use the radon transform to figure out the angle and rotate the image.

% Demo to use the radon transform to determine the angle to rotate an image to straighten it.
% Initialization / clean-up code.
clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 20;
% Read in the color demo image.
[rgbImage, colorMap] = imread('football.jpg');
subplot(2, 3, 1);
imshow(rgbImage, colorMap);
axis on;
title('Original Color Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);
% Extract the red channel and display it.
grayImage = rgbImage(:, :, 1);
subplot(2, 3, 2);
imshow(grayImage, colorMap);
axis on;
title('Red Channel Image', 'FontSize', fontSize);
% Do the Radon transform.
theta = 0:180;
[R,xp] = radon(grayImage,theta);
% Find the location of the peak of the radon transform image.
maxR = max(R(:));
[rowOfMax, columnOfMax] = find(R == maxR)
% Display the Radon Transform image.
h3 = subplot(2, 3, [3,6]);
imshow(R,[],'Xdata',theta,'Ydata',xp,...
            'InitialMagnification','fit')
axis on;
% Plot a blue circle over the max.
hold on;
plot(h3, columnOfMax, xp(rowOfMax), 'bo', 'MarkerSize', 30, 'LineWidth', 3);
line([columnOfMax, columnOfMax], [xp(end), xp(rowOfMax)+15], 'Color', 'b', 'LineWidth', 3);
caption = sprintf('Radon Transform.  Max at angle %.1f', columnOfMax);
title(caption, 'FontSize', fontSize);
xlabel('\theta (degrees)', 'FontSize', fontSize)
ylabel('x''', 'FontSize', fontSize)
colormap(h3, hot(256));
colorbar;
% The column of the max is the angle of the football --
% the angle that the projected sum (profile) will have the highest sum.
% Rotate it by minus that angle to straighten it.
rotatedImage = imrotate(rgbImage, -columnOfMax);
% Display the rotated image.
subplot(2, 3, 4);
imshow(rotatedImage);
axis on;
title('Rotated Color Image', 'FontSize', fontSize);
% Rotate perpendicular to that angle and display that rotation.
rotatedImage = imrotate(rgbImage, -columnOfMax+90);
subplot(2, 3, 5);
imshow(rotatedImage);
axis on;
title('Rotated Color Image', 'FontSize', fontSize);

MATLAB: Radon transform of a circle. Error in imread function

You cannot apply radon() to an RGB image. Look at ndims(A) to see whether it is 2 (2D) or 3 (RGB or RGBA)

Note that some RGB images look grayscale, because they happen to have equal R G and B.

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