One TV screen recognition project, i need to clip the TV Screen from one image.
The TV screen actually is rectangle. But It's obvious that the TV screen is out of shape in the image from phone camera. My question are:
How to detect the any 4 sides polygen(it's not rectangle) in the image.
After i know the polygen area on the image ,how to retrieve the area to Mat.
After solve quest2, How to convert the Mat of 4 sides polygen to rectangle Mat which is fixed W/H radio.
It's very helpful that give some code sample to reference.
Thanks your answers!
if you want to detect the edges of your TV screen you can use some border
detection (like Canny) and then use Hough transform to obtained the lines.
If you then extract the points corresponding to the intersection of the lines
you can create an homography matrix H (3x3). Finally, using this homgraphy you can
"deform" your original image to a reference frame (in our case the rectangle
with a given aspect ratio). The homography is a transformation from plane
to plane, so it's exactly what you will need here.
If your going to use OpenCV (which is always a good choice!),
here are the functions that you could use:
Canny() - find edges in the image
HoughLines() - detect lines
findHomography() - this function finds from a set of correspondances,
the homography matrix. In your case, you will need to pass the method
as 0.
warpPerspective() - the function that your going to use to "deform"
the image to a reference frame.
Obviously, you can find similar functions for MATLAB and others...
I hope this helps you.
Related
I am currently working on a project where I need to find the
square shape tiles in pile which are not overlapped,
am currently working on a project where
I need to determine the orientation , position (center ) ,and color
of each square tile . These orientation and positions
will be used as input for a robot to be picked
and the robot will sort them in a specific locations .
I am using Matlab and i should transfer the data using TCP/IP.
I've experimenting with edge detection(canny,sobel) ,
found the boundaries,segmentation using threshold and FCM but
I haven't found a reliable way to determine the tiles which are
not overlapped ,i am trying to use template shape matching but
i don't know how to do that . This needs to be done in real time
as i will be using frame which is taken from a USB camera that
attached to PC . I was wondering if someone could offer a
reliable solution ? Here is a sample image.
I was wondering if someone could offer
a reliable solution to determine the square shape tiles
which are not overlapped? Here is a sample imageoverlapped Tiles
You've separated the image into tiles and background. So now simply label all the connected components. Take each one and test for single tile-ness. If you know the approximate size of the tiles, first exclude by area. Then calculate the centroid and the extreme left, right, top and bottom. If it is tile, the intersection of top bottom and left-right will be approximately in the centroid, and the half angles will be perpendicular to the tile edge. So rotate, take the bounding box, and count unset pixels, which should be almost zero for a rectangluar tile.
(You'll probably need to do a morphological operation or two to clean up the images if the tile / background separation is a bit dicey).
Check out the binary image processing library http://malcolmmclean.github.io/binaryimagelibrary 1
thanks for your quick replay.i already did some morphological operation and found connected component and below is my code in matlab ,and each tile has 2.5*2.5 cm area
a = imread('origenal image.jpg');
I = rgb2gray(a);
imshow(I)
thresold = graythresh(I);
se1=strel('diamond',2);
I1=imerode(I,se1);
figure(1)
imshow(I1);
bw = imclose(I1 , ones(25) );
imshow(bw)
CC = bwconncomp(bw);
L = labelmatrix(CC);
I am stuck in my application feature. I want cropping feature similar to Cam Scanner Cropping.
The screens of CAM-SCANNER are:
I have created similar crop view.
I have obtained CGPoint of four corners.
But How can I obtained cropped image in slant.
Please provide me some suggestions if possible.
This is a perspective transform problem. In this case they are plotting a 3D projection in a 2D plane.
As, the first image has selection corners in quadrilateral shape and when you transform it in a rectangular shape, then you will either need to add more pixel information(interpolation) or remove some pixels.
So now actual problem is to add additional pixel information to cropped image and project it to generate second image. It can be implemented in various ways:
<> you can implement it by your own by applying perspective tranformation matrix with interpolation.
<> you can use OpenGL .
<> you can use OpenCV.
.. and there are many more ways to implement it.
I had solved this problem using OpenCV. Following functions in OpenCV will help you to achieve this.
cvPerspectiveTransform
cvWarpPerspective
First function will calculate transformation matrix using source and destination projection coordinates. In your case src array will have values from CGPoint for all the corners. And dest will have rectangular projection points for example {(0,0)(200,0)(200,150)(0,150)}.
Once you get transformation matrix you will need to pass it to second function. you can visit this thread.
There may be few other alternatives to OpenCV library, but it has good collection of image processing algorithms.
iOS application with opencv library is available at eosgarden.
I see 2 possibilities. The first is to calculate a transformation matrix that slants the image, and installing it in the CATransform3D property of your view's layer.
That would be simple, assuming you knew how to form the transformation matrix that did the stretching. I've never learned how to construct transformation matrixes that stretch or skew images, so I can't be of any help. I'd suggest googling transformation matrixes and stretching/skewing.
The other way would be to turn the part of the image you are cropping into an OpenGL texture and map the texture onto your output. The actual texture drawing part of that would be easy, but there are about 1000 kilos of OpenGL setup to do, and a whole lot to learning in order to get anything done at all. If you want to pursue that route, I'd suggest searching for simple 2D texture examples using the new iOS 5 GLKit.
Using the code given in Link : http://www.hive05.com/2008/11/crop-an-image-using-the-iphone-sdk/
Instead of using CGRect and CGContextClipToRect Try using CGContextEOClip OR CGContextClosePath
Though i havnt tried this... But i have tried drawing closed path using CGContextClosePath on TouchesBegan and TouchesMoved and TouchesEnd events.
Hope this can give more insight to your problem...
I have a stack of images with a bar close to the center. As the stack progresses the bar pivots around one end and the entire stack contains images with the bar rotated at many different angles up to 45 degrees above or below horizontal.
As shown here:
I'm looking for a way to rotate the bar and/or entire image and align everything horizontally before I do my other processing. Ideally this would be done in Matlab / imageJ / ImageMagick. I'm currently trying to work out a method using first Canny edge detection, followed by a Hough transform, followed by an image rotation, but I'm hoping this is a specific case of a more general problem which has already been solved.
If you have the image processing toolbox you can use regionprops with the 'Orientation' property to find the angle.
http://www.mathworks.com/help/images/ref/regionprops.html#bqkf8ji
The problem you are solving is known as image registration or image alignment.
-The first thing you need to due is to treshold the image, so you end up with a black and white image. This will simplify the process.
-Then you need to calculate the mass center of the imgaes and then translate them to match each others centers.
Then you need to rotate the images to matcheach other. This could be done using the principal axis measure. The principal axis will give you the two axis that explain most of the variance in the population. Which will basically give you a vector showing which way your bar is pointing. Then all you need to due is rotate the bars in the same direction.
-After the principal axis transformation you can try rotating the pictues a little bit more in each direction to try and optimise the rotation.
All the way through your translation and rotation you need a measure for showing you how good a fit your tranformation is. This measure can be many thing. If the picture is black and white a simple subtraction of the pictures is enough. Otherwise you can use measures like mutual information.
...you can also look at procrustes analysis see this link for a matlab function http://www.google.dk/search?q=gpa+image+analysis&oq=gpa+image+analysis&sugexp=chrome,mod=9&sourceid=chrome&ie=UTF-8#hl=da&tbo=d&sclient=psy-ab&q=matlab+procrustes+analysis&oq=matlab+proanalysis&gs_l=serp.3.1.0i7i30l4.5399.5883.2.9481.3.3.0.0.0.0.105.253.2j1.3.0...0.0...1c.1.5UpjL3-8aC0&pbx=1&bav=on.2,or.r_gc.r_pw.r_qf.&bvm=bv.1355534169,d.Yms&fp=afcd637d8ae07bde&bpcl=40096503&biw=1600&bih=767
You might want to look into the SIFT transform.
You should take as your image the rectangle that represents a worst case guess for your bar and determine the rotation matrix for that.
See http://www.vlfeat.org/overview/sift.html
Use the StackReg plugin of ImageJ. I'm not 100% sure but I think it already comes installed with FIJI (FIJI Is Just ImageJ).
EDIT: I think I have misread your question. That is not a stack of images you are trying to fix, right? In that case, a simple approach (probably not the most efficient but definetly works), is the following algorithm:
threshold the image (seems easy, your background is always white)
get a long horizontal line as a structuring element and dilate the image with it
rotate the structuring element and keep dilating image, measuring the size of the dilation.
the angle that maximizes it, is the rotation angle you'll need to fix your image.
There are several approaches to this problem as suggested by other answers. One approach possibly similar to what you are already trying, is to use Hough transform. Hough transform is good at detecting line orientations. Combining this with morphological processing and image rotation after detecting the angle you can create a system that corrects for angular variations. The basic steps would be
Use Morphological operations to make the bar a single line blob.
Use Hough transform on this image.
Find the maximum in the transform output and use that to find orientation angle.
Use the angle to fix original image.
A full example which comes with Computer Vision System Toolbox for this method. See
http://www.mathworks.com/help/vision/examples/rotation-correction-1.html
you can try givens or householder transform, I prefer givens.
it require an angle, using cos(angle) and sin(angle) to make the givens matrix.
I am stuck in my application feature. I want cropping feature similar to Cam Scanner Cropping.
The screens of CAM-SCANNER are:
I have created similar crop view.
I have obtained CGPoint of four corners.
But How can I obtained cropped image in slant.
Please provide me some suggestions if possible.
This is a perspective transform problem. In this case they are plotting a 3D projection in a 2D plane.
As, the first image has selection corners in quadrilateral shape and when you transform it in a rectangular shape, then you will either need to add more pixel information(interpolation) or remove some pixels.
So now actual problem is to add additional pixel information to cropped image and project it to generate second image. It can be implemented in various ways:
<> you can implement it by your own by applying perspective tranformation matrix with interpolation.
<> you can use OpenGL .
<> you can use OpenCV.
.. and there are many more ways to implement it.
I had solved this problem using OpenCV. Following functions in OpenCV will help you to achieve this.
cvPerspectiveTransform
cvWarpPerspective
First function will calculate transformation matrix using source and destination projection coordinates. In your case src array will have values from CGPoint for all the corners. And dest will have rectangular projection points for example {(0,0)(200,0)(200,150)(0,150)}.
Once you get transformation matrix you will need to pass it to second function. you can visit this thread.
There may be few other alternatives to OpenCV library, but it has good collection of image processing algorithms.
iOS application with opencv library is available at eosgarden.
I see 2 possibilities. The first is to calculate a transformation matrix that slants the image, and installing it in the CATransform3D property of your view's layer.
That would be simple, assuming you knew how to form the transformation matrix that did the stretching. I've never learned how to construct transformation matrixes that stretch or skew images, so I can't be of any help. I'd suggest googling transformation matrixes and stretching/skewing.
The other way would be to turn the part of the image you are cropping into an OpenGL texture and map the texture onto your output. The actual texture drawing part of that would be easy, but there are about 1000 kilos of OpenGL setup to do, and a whole lot to learning in order to get anything done at all. If you want to pursue that route, I'd suggest searching for simple 2D texture examples using the new iOS 5 GLKit.
Using the code given in Link : http://www.hive05.com/2008/11/crop-an-image-using-the-iphone-sdk/
Instead of using CGRect and CGContextClipToRect Try using CGContextEOClip OR CGContextClosePath
Though i havnt tried this... But i have tried drawing closed path using CGContextClosePath on TouchesBegan and TouchesMoved and TouchesEnd events.
Hope this can give more insight to your problem...
Maybe I'm asking this too soon in my research, but I'd better know if this is possible sooner than later.
Imagine I have the following square printed on a paper on top of a table:
The table is brown, so it does not match with any of the colors in the square. Is there a way for me, from a common iPhone camera (non-stereo view), to figure out the distance and angle from which Im looking at the square in the table?
In the end what I'm looking for is being able to draw a 3D square on top of this one using the camera image, but I'm not sure if I am going to be able to figure out the distance and position of the object in space using only a 2D image. Any hints are well appreciated.
Short answer: http://weblog.bocoup.com/javascript-augmented-reality
Big answer:
First posterize, Then vectorize, With the vectors in your power you may need to do some math tricks to define, based on the vectors position, the perspective and then the camera position.
Maybe this help:
www.pixastic.com/lib/docs/actions/posterize/
github.com/selead/cl-vectorizer
vectormagic.com/home
autotrace.sourceforge.net
www.scipy.org/PyLab
raphaeljs.com/
technabob.com/blog/2007/12/29/video-games-get-vectorized/
superuser.com/questions/88415/is-there-an-open-source-alternative-to-vector-magic
Oughta be possible. Scan the image for the red/blue/yellow pattern, then do edge detection to figure out how warped the squares are (they'll be parallelograms in anything but straight-on view). Distance would depend on the camera's zoom setting and scan resolution. But basically you'd count how many pixels are visible in each of the squares, run that past the camera's specs and you should be able to determine a rough distance.