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Topic: Find the begining and end of multiple lines
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ray

Posts: 1
Registered: 5/9/13
Find the begining and end of multiple lines
Posted: May 9, 2013 10:44 PM
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Hello world,

So I have been assigned a project that is due in three days. I have completed most of the project but I am running into a problem. The assignment involves finding different shapes on an image and displaying what each shape is. I have found all of the small and large circles in the image and displayed the centroid for each shape. I have also done the same for the squares. The problem is for the lines. I need to know the beginning and ending pixel location for each line. Unfortunately, the line is more than a few pixels wide. I did a canny filter and then hough lines. The problem is that I get the hough lines on each side of the line, not the center. I also tried bwmorph thin and skeleton to try and make the line as thin as possible. After I applied the morph, the image was severely altered. I could not find what I was looking for. Is there any suggestion on how I should approach this
problem? One other problem is that once I find all of the pixel locations, I have to report them in inches from the lower left pixel location. Any idea on how to do that? I am not asking anyone to write code for me, I really am interested in learning what is going on here. However, I will not look down on anyone who would like to provide code.

The image can be seen here:
http://www.flickr.com/photos/63235735@N05/8725185346/
Sorry I don't know how to make that a hyperlink

I am including the code that I have so far below:

clc;
clear all;
close all;

A = imread('C:\Users\Ray\Desktop\board_final_1.png');
imshow(A)
[c1, r1] = imfindcircles(A, [18 22], 'ObjectPolarity' , 'dark', 'Sensitivity', 0.95);
[c2, r2] = imfindcircles(A, [1 4], 'ObjectPolarity' , 'dark', 'Sensitivity', 0.9);
[c3, r3] = imfindcircles(A, [6 9], 'ObjectPolarity' , 'dark', 'Sensitivity', 0.95);
C = [c3 r3];
C = sortrows(C, 1);
figure;
imshow(A, []); viscircles(c1, r1,'EdgeColor','b');
viscircles(c2,r2,'EdgeColor','b');
viscircles(c3, r3, 'Edgecolor','r');
hold on
P12 = plotAndFind(C(1,1), C(1,2), C(1,3), C(2,1), C(2,2), C(2,3));
P34 = plotAndFind(C(6,1), C(6,2), C(6,3), C(7,1), C(7,2), C(7,3));
BoardBW = im2bw(A);
BW1 = bwperim(BoardBW, 8);
for i = 1:649
if (BW1(i,1) == 0)
BW1(i,1) =1;
elseif (BW1(i, 1) == 1)
BW1(i, 1) = 0;
end
if (BW1(648,i) == 0)
BW1(648,i) =1;
elseif (BW1(648,i) == 1)
BW1(648,i) = 0;
end
if (BW1(i,648) == 0)
BW1(i,648) =1;
elseif (BW1(i, 648) == 1)
BW1(i, 648) = 0;
end
end
STATS = regionprops(BW1, 'Perimeter', 'Area', 'Centroid');
Perimeter = cat(1, STATS.Perimeter);
Area = cat(1, STATS.Area);
Centroid = cat(1, STATS.Centroid);
[m n] = size(Perimeter);
j = 1;
k = 1;
h = 1;

for i = 1:m
if(Area(i) == 36)
redcircles(j,:) = Centroid(i,:);
j = j + 1;
else if((Area(i) >100) && (Area(i) < 150))
squares(k,:) = Centroid(i,:);
k = k + 1;
else if((Area(i) >170) && (Area(i) < 190))
blackcircles(h,:) = Centroid(i,:);
h = h + 1;
end
end
end
end
redcircles
squares
blackcircles
[m n] = size(redcircles);
rad = 2*ones(m,1);
viscircles(redcircles, rad, 'EdgeColor', 'b' );
[m n] = size(squares);
rad = 2*ones(m,1);
viscircles(squares, rad, 'EdgeColor', 'b' );
[m n] = size(blackcircles);
rad = 2*ones(m,1);
viscircles(blackcircles, rad, 'EdgeColor', 'b' );

%EVERYTHING FROM HERE DOWN IS WHAT I HAVE BEEN TRYING TO DO.
%EVERYTHING ABOVE IS WHAT I HAVE ALREADY DONE.

%{
I = imread('C:\Users\Ray\Desktop\board_final_1.png');

% Use the EdgeDetection System object to find edges in the
% intensity image. This step outputs a binary image
% required by the HoughTransform System object and
% improves the efficiency of the HoughLines System object.
hedge = vision.EdgeDetector;
csc = vision.ColorSpaceConverter('Conversion', 'RGB to intensity');
hidtypeconv = vision.ImageDataTypeConverter('OutputDataType','single');
img = imread('C:\Users\Ray\Desktop\board_final_1.png');
img1 = step(hidtypeconv, img);
edges = hedge, img1;
imshow(edges);
hhoughtrans = vision.HoughTransform(pi/360,'ThetaRhoOutputPort', true);
hfindmax = vision.LocalMaximaFinder(1,'HoughMatrixInput', true);
hhoughlines = vision.HoughLines('SineComputation','Trigonometric function');

% Find the edges in the intensity image
BW = step(hedge, I);

% Run the edge output through the transform
[ht, theta, rho] = step(hhoughtrans, BW);

% Find the location of the max value in the Hough matrix.
idx = step(hfindmax, ht);

% Find the longest line.
linepts = step(hhoughlines, theta(idx(1)), rho(idx(2)), I);

%* View the image superimposed with the longest line.
imshow(I); hold on;
line(linepts([1 3]), linepts([2 4]))
%}

%I = imread('');
J = imread('C:\Users\Ray\Desktop\board_final_1.png');
I = im2bw(J);




BW2=bwmorph(I,'skel',inf);
figure, imshow (BW2)
endPoints = bwmorph(BW2, 'endpoints');
% Display the image.
subplot(2, 2, 4);
imshow(endPoints, []);
title('Endpoints Image', 'FontSize', 20);
% Find the row and column locations.
[rows cols] = find(endPoints);
numberOfPointsFound = length(rows);
% Plot them.
hold on;
plot(cols, rows, 'bs');



%rotI = imrotate(I,0,'crop');
BW = edge(I,'canny');
figure, imshow(BW)

[H,T,R] = hough(BW);
%figure,imshow(H,[],'XData',T,'YData',R,...
%'InitialMagnification','fit');
xlabel('\theta'), ylabel('\rho');
axis on, axis normal, hold on;
P = houghpeaks(H,100,'threshold',ceil(0.1*max(H(:))));

x = T(P(:,2)); y = R(P(:,1));
plot(x,y,'s','color','white');
% Find lines and plot them
lines = houghlines(BW,T,R,P,'FillGap',50,'MinLength',90);
figure, imshow(I), hold on
max_len = 0;
for k = 1:length(lines)
xy = [lines(k).point1; lines(k).point2]
plot(xy(:,1),xy(:,2),'LineWidth',2,'Color','green');

% Plot beginnings and ends of lines
plot(xy(1,1),xy(1,2),'x','LineWidth',2,'Color','yellow');
plot(xy(2,1),xy(2,2),'x','LineWidth',2,'Color','red');

%{
Determine the endpoints of the longest line segment
len = norm(lines(k).point1 - lines(k).point2);
if ( len > max_len)
max_len = len;
xy_long = xy;
end
%}
end

% highlight the longest line segment
%plot(xy_long(:,1),xy_long(:,2),'LineWidth',2,'Color','blue');
%}




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