2018-11-29 01:55:03 -0500 received badge ● Popular Question (source) 2016-10-12 03:05:49 -0500 commented question Convolution of ROI using as border the pixels outside the ROI That is valid, but I want to avoid the extra calculations because I'm measuring execution time. What you are saying is what I'm currently doing, but since I'm measuring execution time, I would prefer an exact solution. 2016-10-11 04:05:04 -0500 commented question Convolution of ROI using as border the pixels outside the ROI I added an example image and using it tried to explain what I want to do. Said in another way: I would like to be able to calculate the convolution only for the image pixels that the kernel resides entirely inside the image. So, lets say that the example.png describes the case where the kernel size is 3x3. 2016-10-11 03:20:27 -0500 asked a question Convolution of ROI using as border the pixels outside the ROI Hello, is it possible to calculate the convolution of a ROI of an image and use as border the border of the ROI which is outside the ROI (not included in the ROI)? If yes, how is it calculated? For example, I used filter2D on a ROI selected with Rect(), but in filter2D there isn't a border option which matches with what I'm describing above.. example.png edit: To visualize what I'm describing, in the attached file, I want to calculate the convolution of the yellow ROI using as border the pixels around the yellow ROI (the ones included in the blue rectangle but do not belong to the yellow rectangle). Thank you for your time, Panos 2016-02-11 08:24:06 -0500 asked a question filter2D implementation details Hello, Is it possible to have a more detailed description of the implementation of the filter2D() function? Browsing and checking the source code I understood that in general it does the following: if (kernel_size > some_threshold) then do correlation using dft(). else compute filtering using recursion. But in both cases (using dft() or recursion), I'm unable to follow what the code actually does - what is the exact implementation. So, can anyone provide a description of the implementation in each case using some high level pseudocode (or even a list of well defined steps)? If the implementation in each case (using dft() or recursion) depends on some literature (books, papers), could anyone provide these literature sources? Thanks in advance, Panos 2015-11-19 14:31:48 -0500 commented answer error when trying to run cpp-tutorial-pnp_detection Yes you are right - it was my mistake. I did not generate properly the required input files. 2015-11-19 14:31:12 -0500 answered a question error when trying to run cpp-tutorial-pnp_detection Yes you are right - it was my mistake. I did not generated properly the required input files. 2015-11-17 11:06:42 -0500 received badge ● Editor (source) 2015-11-17 11:03:31 -0500 asked a question error when trying to run cpp-tutorial-pnp_detection Hello, I'm trying to run this tutorial: http://docs.opencv.org/3.0-beta/doc/t... with OpenCV 3.0 and I get the following error: OpenCV Error: Assertion failed (channels() == CV_MAT_CN(dtype)) in copyTo, file /home/pmousoul/Downloads/opencv3/opencv/modules/core/src/copy.cpp, line 257 terminate called after throwing an instance of 'cv::Exception' what(): /home/pmousoul/Downloads/opencv3/opencv/modules/core/src/copy.cpp:257: error: (-215) channels() == CV_MAT_CN(dtype) in function copyTo Aborted (core dumped)  Can someone please tell me what I'm I doing wrong? edit: My OpenCV 3.0 version is: OpenCV version: 3.0.0-dev OpenCV VCS version: 3.0.0-699-gb3ac274 Thank you for your time, Cheers, Panos