i have a gui that its goal is to show a multispectral satellite image. i import the image as follow:
[img, R] = geotiffread('myimage.tif');
thus i have the coordinate of 4 corner(R). i wonder how could i display this coordinate in my gui and also get the value of coordinate when i click on the image? the command that i use is:
imshow(img);
should i use another command like mapshow? my final gui should be something like
mapview
that show the coordinate and scale of the image below it. i am able to show the Frame coordinate in a static text box but i have problem about the real coordinate.
many many thanks
Ok unfortunately after a month nobody answered me but I found the answer.
It was really simple. pix2map is a function from Matlab's "Mapping Toolbox" that converts the pixel coordinate to map coordinate.
That was all it took.
Related
I have a really long picture where I use imfindcircles on. But I need to check if the right ones are found. It is a 158708x2560 logical.
So I have:
[centers, radii] = imfindcircles(I,[15 35],'ObjectPolarity','bright','Sensitivity',0.91);
figure(1)
imshow(I)
viscircles(centers,radii);
and I want to save that output you see in the figure box (binary image with circles on it) to a image file. File format doesn't matter as long as it has the same resolution of 158708x2560 pixel.
Every suggestion I find online alters the resolution or makes the image broader, like when saving the figure directly you get a huge grey border and resolution goes down.
What would also work is a way to zoom into the figure but the zoom option in the figure menu does not magnify correctly. It does magnify but the image stays really thin so you can't see a thing.
Matrix: https://www.dropbox.com/s/rh9wakimc7atfhg/I.mat?dl=0
There are two round spots repeating. I want to find those, not the others. And export the image with the circles plotted over it.
I am trying to map my image point by point to 3 dimensional space.
For example, if my original image has intensity of 100 at location X, I want to plot this point in 3D location Y with intensity of 100. I want to repeat this steps for every point/pixel, and get a final image. My biggest problem is that I want to do it point by point.
I appreciate any comments or advice. Thank you.
=======================
p.s.
As I was writing this question, I just came up with an idea. I know how to print 'whole' image into certain location/shape in 3D by using warp() function. Instead of using my whole image as an argument to warp function, if I give one point intensity value and one 3D point as arguments for warp function, and repeat this steps for every image point, will I get a descent looking final image in 3D? If there is a better function to use, please let me know.
Sounds like you are looking for scatter3:
I = imread('cameraman.tif');
[x y]=meshgrid(1:size(I,1), 1:size(I,2));
scatter3(x(:),y(:),I(:),15,I(:),'filled');
axis tight; colormap gray
And this is what you get (after some changes to view point):
PS,
I used a single scatter3 command to plot all the points at once. You may (I have no idea why you would like to do so) do it one by one
figure;
for ii=1:numel(x)
scatter( x(ii), y(ii), I(ii), 15, I(ii), 'filled');
hold on; % need this!
end
axis tight; colormap gray;
I am new to Matlab, I am working on a project which will take input an image like this
as we can see it has a plain background (blue), and system will generate it's passport size image with given ratios, first I am working to separate background and person, the approach I searched is like if there is a blue in combinations of rgb matrices of image, then it is background, and rest is a person, but I am little bit confused that if this approach is correct or not, if it is correct then how can I find that current pixel is blue or not, how can I do it with matlab function find. Any help would be appreciated.
If you want to crop your image based on person's face, then there is no need in separating the background from the foreground. Nowadays you will easily find ready implementations of face detection, so, unless you want to implement your own method because the ready one fails, this should be a non-issue. See:
Show[img,
Graphics[{EdgeForm[{Yellow, Thick}], Opacity[0],
Rectangle ###
FindFaces[img = Import["http://i.stack.imgur.com/cSwzj.jpg"]]}]]
Supposing the face is detected correctly, you can expand/retract its bounding box to match the size you are after.
Hi I want to create a google maps like interface from very high resolution maps. eg. 11k x 11k resolution. My goal is to be able to pan/zoom and put pins on desired locations on the map. I was able to implement zooming/panning of the image using mapbox plugin. my question is how to place a pin on (x,y) location on image and keep the pin while zooming in/out.
Thanks
The easiest way would be to treat the entire image as a 11k by 11k grid with (0,0) in the top right corner. Then, the pin would be located at (x,y). Then, when you scale the image, you treat the new view as a subset of the main grid.
For example, it may start at (5000, 3500) and be 500 by 500 pixels. Then, if the pin is in those coords, you calculate where to place it.
Let's say you have two pins: {(5230, 3550), (5400, 3700)}.
Now, if your zoomed on 5000, 3500 and the view port is 500x500, your pins real locations are:
{(230, 3550), (5400, 3700)}
The way you'll need to do the translations exactly will vary on how exactly your handling zooming/panning, but that should be the general idea.
My Question is as below in two parts……
QUESTION (IN SHORT):
• To generate point cloud of real-world object….
• Through 360 degree rotation of it….on rotating table
• Getting 360 images… one image at each degree (1° to 360°).
• I know how to process image and getting pixel value of it.
• See one sample image below…you can see image is black and white...because I have to deal with the objects which are much shiny (glittery)…and it is DIAMOND. So I have setting up background so that shiny object (diamond) converted in to B/W object. And so I can easily scan outer edge of object (e.g. Diamond).
• And one thing to consider is I don’t using any laser… I just using one rotating table and one camera for taking image…you can see one sample project over here… but there MATLAB hides all the things…because that guy using MATLAB’s in Built functionality.
• Actually I am looking for Math routine or Algorithm or any Technique which helping me out to how getting point cloud…….using the way I have mentioned……..
MORE ELABORATION:
I need to have point-cloud of real-world object. So, I can display it in Computer Screen.
For that I am using one rotating table. I will put my object on it and I will rotate table a complete 360° degree rotation and I will take 360 images…one image at each degree (1° to 360°).
Camera which is used for taking image is well calibrated. I have given one sample image as below. I also know how to scan image and getting pixel value of it.
Also take in consideration that my images are Silhouette type…means just black and white... No color images.
But my problem is or where I am trapped down is in...
Getting Points cloud of object…….from the data which I have getting through processing of image.
One same kind of project I found over here……..
But it just using built in MATLAB functions…I am using Microsoft Visual C#.Net so I have to build the entire algorithm myself….because MATLAB hides all the things which I want to know….
Is there any master…….who know this entire thing well and getting me out of trap...!!!!
Thanks…..
I have no experience of this but If I wanted to do something like this I would have tried this:
Use a single color light source
if Possible create a lightsource which falls on a thin verticle slice of the object.
have 360 B/W Images, those Images will be images of a verticle line having variyng intensity. If you use matlab your matrix will have a/few column with sime values.
now asume a verticle line(your Axis of rotation).
5 plot or convert (imageno, rownoOfMatrix, ValueInPopulatedColumnInSameRow)... [Assuming numbering Image from 0 to 360]
under ideal conditions A lame way To get X and Y use K1 * cos imgNo * ValInCol and K1 * sin imgNo * ValInCol, and Z will be some K2 * rowNum.. K1 and K2 can be caliberated knowing actual size of object.
I mean Something like this:
http://fab.cba.mit.edu/content/processes/structured_light/
but instead of using structured light using a single verticle light
http://www.geom.uiuc.edu/~samuelp/del_project.html This link might help in triangulation...