Being used to Matlab and its great capabilities of drawing vector graphics, I am looking for something similar in OpenCV. OpenCV drawing functions seem to raster the lines or points at pixel level. Currently, I am dumping the data into text, copy-paste to Matlab and doing all the plots. I also thought about using Matlab engine to pass it the parameters and running plots, but it seems to be too much mess for simple debug operation.
I want to be able to do the following:
Zoom in, out of the image
Draw a line/point which is re-rastered each time I do zoom, like in Matlab.
Currently, I found image watch plugin to take care of zooming, but it does not help with the second part.
Any idea?
OpenCV has a lot of capabilities to process an image but only minimal ones for displaying the result. It has nothing that can display vector graphics like Matlab. When I need to see polygons on image (or just polygons) I am dumping them to file and using third party viewer (usually Giv viewer).
Related
I'm trying to figure out a good way to programmatically generate contours describing a 2D surface, from a 3D STEP model. Application is generating NC code for a laser-cutting program from a 3D model.
Note: it's easy enough to do this in a wide variety of CAD systems. I am writing software that needs to do it automatically.
For example, this (a STEP model):
Needs to become this (a vector file, like an SVG or a DXF):
Perhaps the most obvious way of tackling the problem is to parse the STEP model and run some kind of algorithm to detect planes and select the largest as the cut surface, then generate the contour. Not a simple task!
I've also considered using a pre-existing SDK to render the model using an orthographic camera, capture a high-res image, and then operating on it to generate the appropriate contours. This method would work, but it will be CPU-heavy, and its accuracy will be limited to the pixel resolution of the rendered image - not ideal.
This is perhaps a long shot, but does anyone have thoughts about this? Cheers!
I would use a CAD library to load the STEP file (not a CAD API), look for the planar face with the higher number of edge curves in the face loop and transpose them on the XY plane. Afterward, finding 2D geometry min/max for centering etc. would be pretty easy.
Depending on the programming language you are using I would search for "CAD control" or "CAD component" on Google combining it with "STEP import".
I am trying to register two volumetric images from brain (PET and CT or even PET and MR). Each of these volumetric images contains different numbers of 2D images (slices).
For example, CT has 150 slices and PET has 100 slices. I was thinking of using an interpolation method to calculate and reduce the number of CT slices to 100. Is this a correct approach? Does anyone know of any resources that could be helpful for me? like a pseudo code, or steps that I should go through for registering two volumetric images.
Thank you :)
If you know the spacing information for the 150 CT slices and the 100 PET slices, you can look into MATLAB's interp1 function for interpolating along one axis to rescale the images to the same number of pixels. From here it might be possible to use MATLAB's imregister to perform registration.
If you are looking to learn how registration works under the hood (transforming between pixel and physical coordinates, transforming/resampling images, etc.), one resource I can direct you to is the ITK Software Guide pdf.
In particular, try reading Book 1 Section 4.1.4 (page 41 of the pdf) on image representation, and Book 2 Section 3.9 (page 532 of the pdf) on transforms.
In general, the problem of transforming and interpolating with 3D images in registration can be pretty cumbersome to write code for. You need to ask yourself about the spacing and orientation of pixels, how to transform and interpolate images so that their grids overlap, and you also need to decide what to do with pixels in your grid that lie outside the image boundary when evaluating the similarity metric.
While it's up to you to do what you think is best, I suggest you use existing registration programs if they are capable of doing what you want:
MATLAB's imregister (I have never used it so I can't comment on it)
simpleITK for Python
the ITK for C++ has a learning curve but gives full control over the registration process
elastix is a command line program that uses a text file of parameters to perform registration.
3D slicer has a graphical user interface for simple linear registration
I am attempting to do some face recognition and hallucination experiments and in order to get the best results, I first need to ensure all the facial images are aligned. I am using several thousand images for experimenting.
I have been scouring the Internet for past few days and have found many different programs which claim to do so, however due to Matlabs poor backwards compatibility, many of the programs no longer work. I have tried several different programs which don't run as they are calling onto Matlab functions which have since been removed.
The closest I found was using the SIFT algorithm, code found here
http://people.csail.mit.edu/celiu/ECCV2008/
Which does help align the images, but unfortunately it also downsamples the image, so the result ends up quite blurry looking which would have a negative effect on any experiments I ran.
Does anyone have any Matlab code samples or be able to point me in the right direction to code that actually aligns faces in a database.
Any help would be much appreciated.
You can find this recent work on Face Detection, Pose Estimation and Landmark Localization in the Wild. It has a working Matlab implementation and it is quite a good method.
Once you identify keypoints on all your faces you can morph them into a single reference and work from there.
The easiest way it with PCA and the eigen vector. To found X and Y most representative data. So you'll get the direction of the face.
You can found explication in this document : PCA Aligment
Do you need to detect the faces first, or are they already cropped? If you need to detect the faces, you can use vision.CascadeObjectDetector object in the Computer Vision System Toolbox.
To align the faces you can try the imregister function in the Image Processing Toolbox. Alternatively, you can use a feature-based approach. The Computer Vision System Toolbox includes a number of interest point detectors, feature descriptors, and a matchFeatures function to match the descriptors between a pair of images. You can then use the estimateGeometricTransform function to estimate an affine or even a projective transformation between two images. See this example for details.
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 two images of yeast plates:
Permissive:
Xgal:
The to images should be in the same spot and roughly the same size. I am trying to use one of the images to generate a grid and then apply that grid to the other image. The grid is made by looking at the colonies on permissive plate, the plate should have 1536 colonies on it. The problem is that the camera that was used to take the images moves a bit up and down and the images can also be shifted slightly due to the other plate not being in exactly the same place.
This then means that when I use the permissive plate to generate the grid on the xgal plate the grid shifts. Does anyone know a way in which I can compensate for this? I am using perl with the gd module. Any advice would be greatly appreciated. Thank you
I've done this in other languages in relation to motion analysis. You can mathematically determine the shift in position between two images using cross correlation.
Fortunately, you may not need to actually do the maths :) You could use something like ImageMagick, which provides a lot of image processing functions for you, and is perl scriptable. Independently scripts already exists for tasks very much like yours -- see.
If you have only a few pairs of images and, as in the examples, they are very different in appearance then an alternative method to Tim Barrass' would be
Open the first image in gimp, find the co-ordinates of a landmark feature
Open the second image in gimp, find the co-ordinates of the same landmark
Calculate the offset
Shift the second image using ImageMagick's convert command with the affine option. Set the parameters sx=sy=1.0, rx=ry=0.0, tx= negative horizontal offset, ty= negative vertical offset