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.
Related
I am new to image processing. I want to find the surface between black and white pixels which separates them. Here is the link of image.
The size of image is (21,900,900)
https://drive.google.com/file/d/1zUWK0Fb_n6f1JZou5mrUJq0x3h2X8mBK/view?usp=sharing
I tried to use boundarymask command of MATLAB in one plane of image but I am getting noise and also it works for 2d image only. Please suggest me how to find boundary 3d surface here. Thank you.
This is the output image after applying boundarymask.
Your first step should be to get rid of your noise. Since you got some kind of salt and pepper noise you can to that using the median filter on a 2D-image with medfilt2() in matlab. After that you can use an edge ditector to find your edge pixels. The code for this could look like this. If you want the surface, you need to loop this, over the 3rd dimension of your 3D-image. The code will look like this:
for ii=1:16
I=imread('image.tif',ii);
I_bs=boundarymask(I);
I_filt=medfilt2(I_bs,[7 7]);
boundarysurface(:,:,ii)=edge(I_filt,'Canny');
end
The edge detector I used here is certainly overkill for this easy case, but was the easiest thing I could think of in short term. If performance is relevant let me know, and I will give you another approach.
I want to detect the contour of a ring/disc which may be rotated in 3D. I used Detect circles with various radii in grayscale image via Hough Transform by Tao Peng. The results were very close to my requirement. Except for two points:
Using Tao Peng's code I could get a neat blue line indicating the detected contour. I want to access these co-ordinates (sub-pixels) for further processing. I could not figure out where these co-ordinates of detected contour are stored. If you have any idea, please let me know.
Is there any such code to detect ellipse and not only circles? This is because a ring when rotated in 3D wouldn't necessarily be a circle (in which case Tao Peng's code fails. But this is the best I have come across till date. I do not want to binarize my image, as I'll be losing out on a lot of information). Do let me know if there's anything.
Apart from this code, if there's any other one which does a similar job (even if it is like Tao Peng's code, for circles, plus gives me the co-ordinate values), please tell me.
I would prefer MATLAB, but C would also do.
This is an example image who's contour I want to detect, with high accuracy. (The outline of silver disc)
Regards.
Edit:
Here is an example of my output using Tao Peng's code.
I am trying to align an image as a preprocessing step for OCR.
The problem is that I wish to align regions in images that contain text without using a template of an aligned image.
My idea was to first extract the borders of the ROI:
Then, draw some rectangle with fitting proportions(haven't thought on a way to do it automaticlly yet), and try to estimate the geometric transformation between them by using imregcorr:
After that, apply the obtained transformation on the image itself:
As you can see, the final result is far from perfect.
So I wish to know if there is a better way to obtain the coordinates change between the border and the rectangle and apply it on the image.
There's also the possiblity that my approach is too naive, and the solution to this is completely different, so feel free to suggest other methods as you see fit.
Thanks.
Thanks dervish!
I don't really know much about openCV, as I still have to learn C++/python (soon I will, probably).
But I did manage to implement something similar in matlab, using a projective transformation:
m = [mx my]; % Red border corners
s=[sx sy]; % Fixed rectangle borders
BW = poly2mask(mx,my,168,290);
mask = uint8(repmat(BW,[1 1 3]));
TFORM = cp2tform(m,s, 'projective');
Iw = imtransform(I.*mask,TFORM);
[y,x] = find(im2bw(Iw,0));
imshow(Iw(min(y):max(y),min(x):max(x),:))
And here's the 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
I am using regionprop function in matlab to get MajorAxisLength of an image. I think logically this number should not be greater than sqrt(a^2+b^2) in wich a abd b are the width and heigth of the image. but for my image it is. My black and white image contains a black circle in the center of the image. I think this is strange. Can anybody help me?
Thanks.
If you look at the code of regionprops (subfunction ComputeEllipseParams), you see that they use the second moment to estimate the ellipsoid radius. This works very well for ellipsoid-shaped features, but not very well for features with holes. The second moment increases if you remove pixels from around the centroid (which is, btw, why they make I-beams). Thus, the bigger the 'hole' in the middle of your image, the bigger the apparent ellipsoid radius.
In your case, you may be better off using the extrema property of regionprops, and to calculate the largest radius from there.