This question maybe pretty basic, so please bear with me. I have 4 pixel coordinats and an image. I want to segment the image part within this 4 points alone and make a new image. Can you please tell me the easiest way to do this?
Look at roipoly using r and c inputs in addition to input image I.
Assuming you have a coordinate list xcoord matching with ycoord and want to have the smallest square that contains your pixels:
myImage = rand(100)
xcoord = [12 16 22 82];
ycoord = [24 70 12 34];
mySegment = myImage(xcoord(min):xcoord(max),ycoord(min):ycoord(max))
Related
Currently I have a problem with creating a matrix with a quadrant-shape. The problem is as follow:
I would like to have a 138 x 140 matrix with values of 2 and 3. Inside and on the quadrant circle, the values should be 2. Everything outside the circle, I need to have a value of 3. The radius of the circle is 138 (=R138). Hopefully the image below will support my explanation.
I was thinking of using 'triu' (and then flip) in matlab: then I will not get a circle, but a triangle instead (have not tried it yet). And that is not what I want.
What is the simplest way to create this matrix?
You could try this:
a = ones(138, 140)*3;
[gx, gy] = meshgrid(139:-1:0, 137:-1:0);
a(gx.*gx + gy.*gy <= 138*138) = 2;
I have binary images and they have semi or less circles. My aim is to find these circles, make them whole circles and remove all other objects . I found this but it is for MATLAB R2013a. I am using R2011b and it doesn't have the function centers = imfindcircles(A,radius).
How can I do that in MATLAB version R2011b?
Images:
Edit:
My aim is to get whole circle. I show this below for the last image.
Too bad about imfindcircles! One thing I can suggest is to invoke regionprops and specify the 'Area' and 'BoundingBox' flags. regionprops was available in MATLAB for as long as I can remember, so we can certainly use it here.
What this will do is that whatever distinct objects that are seen in the image that are connected, we will find both their areas and their bounding boxes that bound them. After you do this, threshold on the area so that any objects that have a very large area most likely contain circles of interest. Bear in mind that I'm only assuming that you have circles in your image. Should you have any objects that have a large area, this method will extract those out too.
As such, let's read in your image directly from Stack Overflow. When you uploaded the image, it's a RGB image, so I'll have to convert to binary:
im = imread('http://i.stack.imgur.com/wQLPi.jpg');
im_bw = im2bw(im);
Next, call regionprops:
s = regionprops(im_bw, 'Area', 'BoundingBox');
Now, collect all of the areas, and let's take a look at all of the unique areas of all objects seen in this image:
areas = [s.Area].';
unique(areas)
ans =
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
19
20
23
24
25
28
29
38
43
72
73
85
87
250
465
3127
If you take a look at the very end, you'll see that we have an object that has 3127 pixels in it. This probably contains our circle. As such, let's pick out that single element that contains this object:
s2 = s(areas == 3127);
In general, you'll probably have more than one circle in your image, so you should threshold the area to select those potential circles. Something like:
s2 = s(areas > 2000);
Now, let's create a new blank image that is the same size as the original image, then simply use the BoundingBox property to extract out the area that encompasses the circle in the original image and copy it over to the same location in the output image. The BoundingBox field is structured in the following way:
[x y w h]
x and y are the top-left corner of the bounding box. x would be the column and y would be the row. w and h are the width and height of the bounding box. As such, we can use this directly to access our image and copy those pixels over into the output image.
out = false(size(im_bw));
bb = floor(s2.BoundingBox); %// Could be floating point, so floor it
out(bb(2):bb(2)+bb(4)-1, bb(1):bb(1)+bb(3)-1) = im_bw(bb(2):bb(2)+bb(4)-1, bb(1):bb(1)+bb(3)-1);
This is what I get:
What you should probably do is loop over the circles in case we have more than one. The above code assumes that you detected just one circle. Therefore, do something like this:
out = false(size(im_bw));
for idx = 1 : numel(s2) %// For each potential circle we have...
bb = floor(s2(idx).BoundingBox); %// Could be floating point, so floor it
%// Copy over pixels from original bw image to output
out(bb(2):bb(2)+bb(4)-1, bb(1):bb(1)+bb(3)-1) = im_bw(bb(2):bb(2)+bb(4)-1, bb(1):bb(1)+bb(3)-1);
end
A small thing to note is that the bounding box encompasses the entire object, but there could also be some noisy pixels that are disconnected that are within that bounding box. You may have to apply some morphology to get rid of those pixels. A binary opening could suffice.
Here's what I get with your other images. I thresholded the area to search for those that have 2000 pixels or more (I did this above):
Just for self-containment and your copy-and-pasting pleasure, here's the code in one segment:
clear all;
close all;
%im = imread('http://i.stack.imgur.com/qychC.jpg');
%im = imread('http://i.stack.imgur.com/wQLPi.jpg');
im = imread('http://i.stack.imgur.com/mZMBA.jpg');
im_bw = im2bw(im);
s = regionprops(im_bw, 'Area', 'BoundingBox');
areas = [s.Area].';
s2 = s(areas > 2000);
out = false(size(im_bw));
for idx = 1 : numel(s2) %// For each potential circle we have...
bb = floor(s2(idx).BoundingBox); %// Could be floating point, so floor it
%// Copy over pixels from original bw image to output
out(bb(2):bb(2)+bb(4)-1, bb(1):bb(1)+bb(3)-1) = im_bw(bb(2):bb(2)+bb(4)-1, bb(1):bb(1)+bb(3)-1);
end
imshow(out);
All three images are there in the code. You just have to uncomment whichever one you want to use, comment out the rest, then run the code. It will display an image with all of your detected circles.
Edit
You would like to draw complete circles, instead of extracting the shape themselves. That isn't a problem to do. All you need to do is determine the best "radii" that can be enclosed inside each of the bounding boxes. This is simply the maximum of the width and height of each bounding box, then divide these quantities by 2.
After, create a 2D grid of co-ordinates through meshgrid that is the same size as the original image itself, then create a binary image such that the Euclidean distance between the centre of this bounding box with any point in this 2D grid less than the radius is set to logical true while the other positions are set to logical false.
In other words, do this:
clear all;
close all;
im = imread('http://i.stack.imgur.com/qychC.jpg');
%im = imread('http://i.stack.imgur.com/wQLPi.jpg');
%im = imread('http://i.stack.imgur.com/mZMBA.jpg');
im_bw = im2bw(im);
s = regionprops(im_bw, 'Area', 'BoundingBox');
areas = [s.Area].';
s2 = s(areas > 2000);
out = false(size(im_bw));
for idx = 1 : numel(s2) %// For each potential circle we have...
bb = floor(s2(idx).BoundingBox); %// Could be floating point, so floor it
%// Copy over pixels from original bw image to output
out(bb(2):bb(2)+bb(4)-1, bb(1):bb(1)+bb(3)-1) = im_bw(bb(2):bb(2)+bb(4)-1, bb(1):bb(1)+bb(3)-1);
end
figure;
imshow(out);
%// Image that contains all of our final circles
out2 = false(size(im_bw));
[X,Y] = meshgrid(1:size(im_bw,2), 1:size(im_bw,1)); %// Find a 2D grid of co-ordinates
for idx = 1 : numel(s2) %// For each circle we have...
bb = floor(s2(idx).BoundingBox); %// Could be floating point, so floor it
cenx = bb(1) + (bb(3) / 2.0); %// Get the centre of the bounding box
ceny = bb(2) + (bb(4) / 2.0);
radi = max(bb(3), bb(4)) / 2; %// Find the best radius
tmp = ((X - cenx).^2 + (Y - ceny).^2) <= radi^2; %// Draw our circle and place in a temp. image
out2 = out2 | tmp; %// Add this circle on top of our output image
end
figure;
imshow(out2);
This script now shows you the original extracted shapes, and the best "circles" that describes these shapes in two separate figures. Bear in mind that this is a bit different than what I showed you previously with one circle. What I have to do now is allocate a blank image, then incrementally add each circle to this new image. For each circle, I create a temporary binary image that has just a circle I'm looking for, then I add this on top of the new image. At the end, we will show all of the circles in the image that are fully drawn as you desire.
This is what I get for the best circle for each of your images:
Good luck!
What is the shortest way to find coordinates of figure left/right/top/bottom edges? 4 coordinates (2 horizontal, 2 vertical lines) are enough.
Tried to flip, transpose, etc. My mind is gonna blow :/.
[EDIT]: Image is binary. Figure is represented by 1's.
You can try to get its bounding box with the regionprops() function.
regionprops(img,'BoundingBox')
The result is (x,y) upper left coordinates x_width, y_width, size of the box.
I get [45.5000000000000 45.5000000000000 174 107] in your image.
The shortest solution i made:
% I - image array
V = sum(I,2);
edge_top = find(V,1,'first');
edge_bot = find(V,1,'last');
H = sum(I,1);
edge_left = find(H,1,'first');
edge_right = find(H,1,'last');
I have an image with a white border around it, and I need to get rid of the border. There are 20 rows of white pixels above the image, 5 columns of white to the left, 5 of white columns to the right, and 5 rows of white below the image. I wan't to crop the image exactly out of that border, how do I do this in matlab? Thanks for any help you can give!
(The image is a tiff, which is why I can't use an online service for this, they won't let me upload .tiff)
What you need is the built-in MATLAB function imcrop. To use it, specify something like
B = imcrop(A,[xmin ymin width height]);
if A is your original image. First find the dimensions of your image. Say its 800 by 600. Then you are looking to crop a 770 by 580 image so these numbers respectively will be your width and height in the above function. Your x and y would be something like 5 and 20, respectively.
U can use imcrop for this if you have image processing toolbox or you can make new image as follows:
I2 = I(21:end-5, 6:end-5)
For 3 dimensions, you can use:
I2 = I(21:end-5,6:end-5,:)
For example as per your comment:
I = rand(153,1510,3);
size(I); % 153 1510 3
I2 = I(21:end-5,6:end-5,:);
size(I2); % 128 1500 3
newIm = oldIm(20:length(oldIm(:,1))-5,5:length(oldIm(1,:))-5)
I have a figure of size 14 x 14 square drawn inside an axis of 20 x 20, in matlab.
I am trying to draw circles of radius 0.7 inside the square and need to arrange them evenly. I need to draw 233 circles. Please let me know how can I do it?
Currently I can draw them randomly but couldn't get 233 circle. Please see my below code.
Your reply is appreciated.
% Urban, sub urban, Rural areas
x_area =[3, 12, 6];
y_area = [6, 8, 16];
r_area = [1, 7, 2];
f = figure;
hAxs = axes('Parent',f);
hold on, box on, axis equal
xlabel('x')
ylabel('y','Rotation',0)
title('Compute the area of circles a vectorized way for several cicles')
axis([0 20 0 20])
rectangle('Position',[5,1,14,14])
rectangle('Position',[3,1,2,2])
rectangle('Position',[1,3,4,4])
hold on, box on, axis equal
a = 233;
x_base_urban = randi([6 18], 1, a);
b = rand([10 8], 1);
y_base_urban = randi([2 14],1, a);
r_base_urban = 0.9;
size_x = size(x_base_urban);
size_x = size_x(2);
size_y = size(y_base_urban);
size_y = size_y(2);
colour = rand(size_x,3);
for t = 1: size_x
plot(x_base_urban(t)+ r_base_urban.*cos(0:2*pi/100:2*pi),...
y_base_urban(t)+ r_base_urban.*sin(0:2*pi/100:2*pi),'parent',hAxs)
plot(x_base_urban(t),y_base_urban(t),'+','parent',hAxs)
end
Thanks
Randomly plotting everything won't work. Actually, if your circles can't overlap, nothing will work. To show that, just compare the results of following calculations:
lSquare = 14;
rCircle = 0.7;
nCircles = 233;
areaCircles = nCircles * pi * rCircle^2
areaSquare = lSquare^2
You will see that areaCircles > areaSquare, so it is impossible to fit them all in. On the other hand, if areaSquare >= areaCircles does not guarantee you that a solution exists!
Try your setup with a smaller example to come up with a solution. E.g. take a square box and a bunch of spherical objects (balls, marbles, oranges, apples, ... if need be) and try to fit as much of those in your box. If that works, you might even want to draw their positions on a sheet of paper before trying to implement it.
If you do this correctly, you will get an idea of how to stack round objects in a square container. That is also exactly what you need to do in your exercise. Then try to make a model/algorithm of what you did manually and implement that in MATLAB. It won't be hard, but you will need some small calculations: Pythagoras and intersection of circles.
I also suggest you use a function to draw a circle as #Andrey shows, so something of the form function drawCircle(center, radius). That allows you to keep complexity down.
If your circles can overlap, then the solution is quite easy: look at a circle as an object with a center point and distribute these center points evenly over the square. Don't use rand to do this, but calculate their positions yourself.
If you can't find a solution, I might expand my answer in a few days.
Without diving too deep into your code, I think that you need to add a hold function, after the first plot
for t = 1: size_x
plot(x_base_urban(t)+ r_base_urban.*cos(0:2*pi/100:2*pi),...
y_base_urban(t)+ r_base_urban.*sin(0:2*pi/100:2*pi),'parent',hAxs)
plot(x_base_urban(t),y_base_urban(t),'+','parent',hAxs)
hold(hAxs,'on');
end
By the way, the best way to draw circle is by using rectangle command.
rectangle('Curvature',[1 1],'Position',[1 3 4 5])
So you can create a PlotCircle function (like #EgonGeerardyn suggests) like this:
function plotCircle(x,y,r)
rectangle('Position',[x-r y-r 2*r 2*r],'Curvature',[1 1]);
end