I need to create a binary mask of the center cancer cell in this image, the example given to me uses a for loop to do this, however, I can't figure out what to change the numbers to in order to mask out just the middle part. It keeps just masking out the side.
Here's the for loop:
However, when I just run the for loop with my image in the place of b(), I get this
Please help!
Related
I'm trying to make an object recognition program using a k-NN classifier. I've got a bunch of images for the training part of the classifier and a bunch of images to recognize. Those images are in grayscale and there's an object (only its edge) per image. I need to calculate their center of mass so I use
img=im2bw(img)
and then regionprops(img,'centroid').
The problem is that some of those edges aren't closed so regionprops doesn't work then. I tried eroding the image (the edge is black, white background) but the endlines of those edges are too apart from eachother. I tried using bwmorph function to do so but still can't make it work.
Any ideas?
EDIT
I'm adding some images in case anyone wants to try:
Use morphological operation
Use a closing operation to make your structures filled.
1. As first step prepare your image data
im = imread('your image.jpg');
% Get first channel as gray scale information
im = im(:,:,1);
% Threshold it for simplicyty, you may work on grayscale too.
im1 = logical(im > 128);
2. Use a simple block shaped structuring element
The structuring element is defined by:
strel=ones(3,3);
You may use disk shaped elements or whatever gives the best result to you.
3. Apply structuring element a couple of times
Apply the strel a couple of times with an erosion operator to your original image to close your figure:
for i=1:20
im1 = imerode(im1,strel);
end
4. Dilate the image to get back to original shape
Next step is to dilate the image to get back to your original outer shape:
for i=1:20
im1 = imdilate(im1,strel);
end
Final result
The final result should be suitable to get a sufficiently precise center or gravity.
I am struggling to find a good contour detection function that would count the number of contour in bw images that I have processed using some previous tools. As you can see, my profile picture is an example of such images,
,
In this image, ideally, I wish to have a function which counts four closed contour.
I don't mind if it also detects the really tiny contours in between, or the entire shape itself as extra contours. As long as it counts the medium sized ones, I can fix the rest by applying area threshold. My problem is that any function I have tried detects only one contour - the entire shape, as it cannot separate it to the su-conours which are connected to one another.
Any suggestions?
Here is my shot at this, although your question might get closed because it's off-topic, too broad or a possible duplicate. Anyhow I propose another way to count the number of contours. You could also do it using bwboundaries as was demonstrated in the link provided by #knedlsepp in the possible duplicate. Just for the sake of it here is another way.
The idea is to apply a morphological closure of your image and actually count the number of enclosed surfaces instead instead of contours. That might end up being the same thing but I think it's easier to visualize surfaces.
Since the shapes in your image look like circle (kind of...) the structuring element used to close the image is a disk. The size (here 5) is up to you but for the image you provided its fine. After that, use regionprops to locate image regions (here the blobs) and count them, which comes back to counting contours I guess. You can provide the Area parameter to filter out shapes based on their area. Here I ask the function to provide centroids to plot them.
Whole code:
clear
clc
close all
%// Read, threshold and clean up the image
Im = im2bw(imread('ImContour.png'));
Im = imclearborder(Im);
%// Apply disk structuring element to morphologically close the image.
%// Play around with the size to alter the output.
se = strel('disk',5);
Im_closed = imclose(Im,se);
%// Find centroids of circle-ish shapes. Youcan also get the area to filter
%// out those you don't want.
S = regionprops(~Im_closed,'Centroid','Area');
%// remove the outer border of the image (1st output of regioprops).
S(1) = [];
%// Make array with centroids and show them.
Centro = vertcat(S.Centroid);
imshow(Im)
hold on
scatter(Centro(:,1),Centro(:,2),40,'filled')
And the output:
So as you see the algorithm detected 5 regions, but try playing a bit with the parameters and you will see which ones to change to get the desired output of 4.
Have fun!
I would like to crop an image but I want to retain the part of image that is outside of the rectangle. How can this can be done?
It seems that with imcrop only the part within the rectangle can be retained.
An image in Matlab is represented by a matrix, just like any other matrix, you can read more about representation forms here.
It seems that what you want to do is to take the area that you don't want and change the values of the corresponding cells in the matrix to the color that you want to put instead (each cell in the matrix is a pixel in the image). That is if you know the place where your unwanted data is.
If you don't know where it is, and want to use the tool given by imcrop to manually choose the "cropped" area, you can take the resulting matrix, and find the part of the original image which is an exact match with the cropped part, and to color it as you wish.
The code for doing this:
I=imread('img_9.tif');
I2=imcrop(I,[60,50,85,85]);
n_big=size(I);
n_small=size(I2);
for j1=1:(n_big(1)-n_small(1))
for j2=1:(n_big(2)-n_small(2))
Itest=I(j1:j1+n_small(1)-1,j2:j2+n_small(2)-1,:);
if ( Itest == I2)
I(j1:j1+n_small(1)-1,j2:j2+n_small(2)-1,:) = zeros(n_small(1),n_small(2),3);
end
end
end
figure(1);
imshow(I);
figure(2);
imshow(I2);
The results of my test were:
original:
cropped:
resulting image:
maybe what you want to do is first a mask with the inverse area of what you want to crop and save this result.
My image is a 2D surface of a protein, and I use matlab function "scatter" to display the image, so there are some white empty spaces in it.
I want to fill them with colors，but the question is that the points have different colors, some are red and some are orange(point color is decided by its RGB value).
So I wanna assign the color of the white space similar to their corresponding neighbors.
the original work i did is to extract the edge of the polygon first，which helps me detect if the point is inside the polygon or not, because I am not assigning colors to white spaces that are outside the polygon.
And then simply scan the whole image pixels one by one to check if the pixel is the white， if so, I just assign the neighbor color to it,like what i said, I have to check if the pixel is inside the polygon or not every time.
But the speed is really slow, and the result is not good enough,could anybody give me some idea on it ?
I have the 2D scatter points image and also the 3D structure.Each point in 2D can find one
counterpart in 3D, I don't know if this information would help.
After an erosion with a disk kernel(7x7) such as and then a bilateral filter:
PS: if you have the 3D points structure, upload it somewhere and post a link
please help with Matlab beginner challenge
i need to create an image with few geometrical objects (circles,
ellipses) and then to apply some projective transforms
my problem is that i cant understand how to actually "draw" on image
image is AFAIU generally defined as [X;Y;3] matrix,
functions as SCIRCLE1 can compute/return collection of points
representing circle, but the problem is that points are not discrete ,
coordinates are real numbers and not pixels
how can i recompute the scircle output to be valid in image
coordinates system ? i.e. how can i "pixelize" it?
thanks for your attention, i really missing some basic concept and
will appreciate your help
John
well, below is an answer i received on Matlab newsgroups
BOTTOM LINE-no built-in way in Matlab
======================================
'getframe' can be used to merge axes even though it is more commonly used to create movie frames.
MATLAB is really weak in this area. There are some primitive
functions for drawing into the overlay (such as rectangle() if you
want to draw a circle, and line() if you want to draw a line) but no
real way that I know of to draw right into the underlying image. So
you have to use "tricks" such as getframe and then apply logical
operations. And you have to be careful with that since I think when
it gives you the rasterized version of the overlay it might be the
size of the image on the screen, not the true original matrix size of
the underlying image (I'd have to recheck this).
full thread here : http://www.mathworks.com.au/matlabcentral/newsreader/view_thread/261232
I found this example which give you a easy way to put simple geometrical object onto pictures.
Read the input image.
I = imread('cameraman.tif');
Define the rectangle dimensions as [x y width height].
rectangle = int32([10 10 30 30]);
Draw the rectangle and display the result.
J = step(shapeInserter, I, rectangle);
imshow(J);
see this link
by the way..
I didn't get you point about points not being discrete and images being a matrix. The way I see it. It much the same. you could try to explain it more in depth ?
The insertShape function in the Computer Vision System Toolbox is what you need. It lets you draw rectangles, circles, and polygons into the image.
There is also insertText, insertMarker, and insertObjectAnnotation.