I have two images, one that is a monochrome one which is a mask and another one with full color. What I need to do is find the CGRect of the mask (white pixels) in the other full color one.
What I did is to first find the contour of the mask using the Vision framework. Now, this returns a CGPath which is normalised. How can I translate this path into coordinates to the other image? Both have been scaled the same way to make them the same size so the translation should be "easy" but I can't figure it out.
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Given an image with say just two coloured points in it.. Is it possible to crop the image from the coordinates of the first colured point to the coordinates of the second coloured point .
A sample image where i have to crop between two green points
This is possible, if the colored points have a distinct range of color when compared with the rest of the image.
Algorithm:
1. Convert the image to HSV color space
2. Scan the image while looking for pixels in the range of hue and saturation of the color/s of the points.
3. Record minimum and maximum X,Y coordinates of the points that match.
4. calculate the bounding box of the region using the coordinates.
5. Crop the image using the bounding box.
You can try to follow these steps and edit the question with code if/when you come up with errors. Uploading a sample image somewhere and linking to it will help us provide better answers.
I want to cut a renctangular shape out of an image.
I know the position of the rectangle relative to the orginal image.
However: When I rotate/scale/translate the image, the image dimensions changes. So my crop to the rectangle does not work anymore.
Is there a way to preserve the "old" coordinate system while transforming the image and then do a crop based on that old system?
The Image is always rotated/scaled around its center. Translation is applied after scaling and rotation.
I aim for a solution in php with imagick. However: When its not possible I am fine with command line imagemagick, too
I am trying to crop a picture on right on along the contour. The object is detected using surf features and than i want to crop the image of extactly as detected.
When using crop some outside boundaries of other object is includes. I want to crop along the green line below. OpenCV has RotatedRect but i am unsure if its good for cropping.
Is there way to perfectly crop along the green line
I assume you get you get your example from http://docs.opencv.org/doc/tutorials/features2d/feature_homography/feature_homography.html, so what you can do is to find the minimum axis aligned bounding box around the green bounding box, crop it from the image, use the inverted homography (H.inv()) matrix to transform that sub image into a new image (call cv::warpPerspective), and then crop your green bounding box (it should be axis aligned in your new image).
You can get the equations of the lines from the end points for each. Use these equations to check whether any given pixel lies within the green box or not i.e. does it lie between the left and right lines and between the top and bottom lines. Run this over the entire image and reset anything that doesn't lie within the box to black.
Not sure about in-built functionality to do this, but this simple methodology is guaranteed to work. For higher accuracy, you may want to consider sub-pixel checks.
I want to overlay an image in a given image. I have created a mask with an area, where I can put this picture:
Image Hosted by ImageShack.us http://img560.imageshack.us/img560/1381/roih.jpg
The problem is, that the white area contains a black area, where I can't put objects.
How can I calculate efficiently where the subimage must to put on? I know about some functions like PointPolygonTest. But it takes very long.
EDIT:
The overlay image must put somewhere on the white place.
For example at the place from the blue rectangle.
Image Hosted by ImageShack.us http://img513.imageshack.us/img513/5756/roi2d.jpg
If I understood correctly, you would like to put an image in a region (as big as the image) that is completely white in the mask.
In this case, in order to get valid regions, I would apply an erosion to the mask using a kernel of the same size as the image to be inserted. After erosion, all valid regions will be white.
The image you show however has no 200*200 regions that is entirely white, so I must have misunderstood...
But if you what to calculate the region with the least black in the mask, you could apply a blur instead of an erosion and look for the maximal intensity pixel in the blurred mask.
In both case you want to insert the sub-image so that its centre is on the position maximal intensity pixel of the eroded/blurred mask.
Edit:
If you are interested in finding the region that would be the most distant from any black pixel to put the sub-image, you can define its centre as the maximal value of the distance transform of the mask.
Good luck,
The application PhotoFiltre has an option to stretch part of an image. You select a rectangular shape and you can then grab and move the vertexes somewhere else to make any quadrangle. The image part which you selected will stretch along. Hopefully these images make my point a little clearer:
Is there a general algorithm which can handle this? I would like to obtain the same effect on HTML5 canvas - given an image and the resulting corner points, I would like to be able to draw the stretched image in such a way that it fills the new quadrangle neatly.
A while ago I asked something similar, where the solution was to divide the image up in triangles and stretch each triangle so that each three points correspond to the three points on the original image. This technique turned out to be rather exprensive and I would like if there is a more general method of accomplishing this.
I would like to use this in a 3D renderer, but I would like to work with a (2D) quadrangle.
I don't know whether PhotoFiltre internally also uses triangles, or whether it uses another (cheaper) algorithm to stretch an image like this.
Does someone perhaps know if there is a cheaper or more general method/algorithm to stretch a rectangular image, so that it fills a quadrangle given four points?
The normal method is to start with the destination, pick an appropriate grid size and then for each point in the new shape calculate the corresponding point in the source image (possibly with interpolation depending on the quality you need)
Affine transform.
Given four points for the "stretched" figure and four points for the figure it should match (e.g. a rectangle), an affine transform provides the spatial mapping you need. For each point (x1,y1) in the original image there is a corresponding point (x2,y2) in the second, "stretched" image.
For each integer-valued pixel (x2, y2) in the stretched image, use the affine transform to find the corresponding real-valued point (x1, y1) in the original image and apply its color to (x2,y2).
http://demonstrations.wolfram.com/AffineTransform/
You'll find sample code for Java and other languages online. .NET has the Matrix class.