lpb's profile - activity

well the src image I want to deform to a square shape is not a 2D or 3D transformed plane, warping the iamge according to a geometrical transformation is not what I am looking for. I want to apply the content of an image between 4 control points so that it is interpolated to a plane, just like applying a texture on a plane in OpenGL/DirectX by proviing UV custom texture coordinate of an image.

are you referring to finding the prominent color in an image and selecting between green, red or blue?

for a first step, you can get the color distribution (histogram) of your image by using calcHist docs.opencv.org/modules/imgproc/doc/histograms.html?highlight=calchist#calchist

Hi, I was wondering if there was a function in OpenCV that would allow me to deform an image in this way: take 4 points that defines the trapeze boundary of a region in an image and apply them as texture coordinate of a plane so that it is interpolated correctly on a square plane (wrap this region's inside of this new square region). I can do this in OpenGL by defining UV coordinates of a texture to be applied on a plane but I was wondering it the equivalent existed in OpenCV.

Remap() seems to take as arguments a table of correlated points in both images for each axis. In my case, both images might not be of the same size and the src image points are not on a symmetrical boundary. Also, the source plane is not necessarily the destination one transformed in 2D, so no geometrical manipulation.

Thank you

Hi, I am detecting a square pattern in an image and retrieving its pose using SolvePnP(), which gives me a translation vector in pixel unit and a rotation vector. I would now like to transform my source image using this translation and rotation so that I can display only the sub-part containing the pattern "flatten out" in 2D. The result would be a square image of the pattern as it is in the source image but re-alligned in 2D. I would obtain this by using warPerspective().

I tried getPerspective() + warPerspective instead and it works partially well: the sub-part is indeed retrieved but since this gets me a 2D transform and the pattern in the scene is rotated in 3D, it does not compensate properly and I get a square image of a plane at an angle.

I looked at this: http://jepsonsblog.blogspot.com/2012/11/rotation-in-3d-using-opencvs.html to build the perspective transform out of the 3D translation and rotation. I get confusing results in the final image transform when building the image transformation. If I skip the translation and rotation component, using only a transformation matrix (trans) composed of:

//------
// Projection 2D -> 3D
matrix Mat A1 = (Mat_<double>(4,3) <<
1, 0, -w/2,
0, 1, -h/2,
0, 0, 0,
0, 0, 1);

// 3D -> 2D
matrix Mat A2 =
(Mat_<double>(3,4) <<
f, 0, w/2, 0,
0, f, h/2, 0,
0, 0, 1, 0);

Mat trans = A2 * A1;

// warp perspective according to trans... The result is wrong..
warpPerspective(input, output, trans, input.size(), INTER_LANCZOS4);
//------

I get a black image. To give you an idea of actual values given my calibration:

camera Matrix:
[954.81 | 0 | 306.26
0 | 923.77 | 236.55
0 | 0 | 1]

A2:
[954.81 | 0 | 306.26 | 0
0 | 923.77 | 236.55 | 0
0 | 0 | 1 | 0]

A1:
[1 | 0 | -306.26
0 | 1 | -236.55
0 | 0 | 0
0 | 0 | 1]

final perpective image transform (trans):
(954.81 | 0 | -292420.
0 | 923.77 | -218518.
0 | 0 | 0)

there is clearly something wrong with the last column of this transformation matrix, can you point me out what it is, I don't understand? Thank you very much,