I want to achieve
source.rgba * dest.rgba
with cairo. Is that possible without writing the loop manually? The multiplication operator still uses alpha-over, which is not the right thing.
One of the operands is a possibly rotated mask, and the other one is a shadow map that is not rotated. Here are the pictures. The mask will be visible if you open it in Gimp, where multiplication does exactly what I want.
Related
As part of my initial research, to see if using Cairo is a good fit for us, I'm looking to see if I can obtain an (x,y) point at a given distance from the start of a path. I have looked over the Cairo examples and APIs but I haven't found anything to suggest this is possible. It would be a pain if we had to build our own Bezier path implementation from scratch.
On android there is a class called PathMeasure. This allows getting an (x,y) point at a given distance from the start of the path. This allows me to draw a stamp easily at the wanted distance being able to produce something like the image below.
Hopefully someone can point me in the right direction.
Unless I have an uncomplete understanding of what you mean with "path", it seems that you can accomplish the task by starting from this guide. You would use multiple cr (image location, rotation, scale) and just one image instance.
From what I can understand from your image, you'll need to use blending (e.g. the alpha channel), I would say setting pixel by pixel the alpha channel (transparency) proportional to/same as your original grayscale values, and all the R G B pixels values to black (0).
For acting directly on your input image (on the file you will be loading), by googling "convert grayscale image to alpha" I found several results for Photoshop, some for gimp, I don't know what would you have available.
Otherwise you will have to do directly within your code accessing the image pixels. To read/edit pixel values you can use cairo_image_surface_get_data. First you have to create a destination image with cairo_image_surface_create
using format CAIRO_FORMAT_ARGB32
Similarly, you can use cairo_mask drawing a black rectangle of the size of your image, after having created an alpha channel image of format CAIRO_FORMAT_A8 from your original image (again, accessing pixel by pixel seems the only possible way given the limitations of cairo_image_surface_create_from_png).
Using cairo_paint_with_alpha in place of cairo_paint is not suitable because the alpha channel would be constant for the whole image.
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 want to make output of left hand image like right hand by performing affine operations like, scaling , translation ,shear and rotation.
If you are asking how to perform image registration in matlab then have a look at this great toolbox off the file exchange. Image registration is the process of uncovering the transformation parameters than will align a source image to a reference image as closely as possible. If you use affine registration, the result will be an affine transformation matrix that will transform your left image to your right image. One thing to watch out for is that by default the registration may take the upper left corner of the image for the centre of rotation but you will more likely want the centre of the image to be the centre of rotation in which case simply translate the image by half its dimensions before and after applying a transformation / registration.
However if you literally just want to know the angle of rotation for this one single image, then use a protractor.
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 am working on an iOS project which uses ImageMagick. I wonder if it is possible to perform some circular distortions on an image, but not on the center of the image, rather in a point (x,y) and of a given radius R.
Any (constructive) responses are well appreciated.
Many thanks
If ImageMagick doesn't directly support doing a circular distortion at non-origin, you might want to pass in a sequence of commands to: a) add appropriate border to the image, b) do a circular distortion, c) get rid of the border added in (a). The size of the border is such that it effectively shifts the distortion origin to the desired place in the original image.