template-matching

来源： https://stackoverflow.com/questions/59679516/opencv-edge-based-object-detection-c

来源： https://stackoverflow.com/questions/59679516/opencv-edge-based-object-detection-c

来源： https://stackoverflow.com/questions/59679516/opencv-edge-based-object-detection-c

问题 I'm trying to do template matching basically on java. I used straightforward algorithm to find match. Here is the code: minSAD = VALUE_MAX; // loop through the search image for ( int x = 0; x <= S_rows - T_rows; x++ ) { for ( int y = 0; y <= S_cols - T_cols; y++ ) { SAD = 0.0; // loop through the template image for ( int i = 0; i < T_rows; i++ ) for ( int j = 0; j < T_cols; j++ ) { pixel p_SearchIMG = S[x+i][y+j]; pixel p_TemplateIMG = T[i][j]; SAD += abs( p_SearchIMG.Grey - p_TemplateIMG

问题 Function rotates the template image from 0 to 180 (or upto 360) degrees to search all related matches(in all angles) in source image even with different scale. The function had been written in OpenCV C interface. When I tried to port it to openCV C++ interface , I am getting lot of errors. Some one please help me to port it to OpenCV C++ interface. void TemplateMatch() { int i, j, x, y, key; double minVal; char windowNameSource[] = "Original Image"; char windowNameDestination[] = "Result

问题 Function rotates the template image from 0 to 180 (or upto 360) degrees to search all related matches(in all angles) in source image even with different scale. The function had been written in OpenCV C interface. When I tried to port it to openCV C++ interface , I am getting lot of errors. Some one please help me to port it to OpenCV C++ interface. void TemplateMatch() { int i, j, x, y, key; double minVal; char windowNameSource[] = "Original Image"; char windowNameDestination[] = "Result

问题 I have this image of a table (seen below). And I'm trying to get the data from the table, similar to this form (first row of table image): rows[0] = [x,x, , , , ,x, ,x,x, ,x, ,x, , , , ,x, , , ,x,x,x, ,x, ,x, , , , ] I need the number of x's as well as the number of spaces. There will also be other table images that are similar to this one (all having x's and the same number of columns). So far, I am able to detect all of the x's using an image of an x. And I can somewhat detect the lines. I

问题 I am trying to implement template matching using phase correlation. I have already done it in the spatial domain. You can see here My template image is imagePart and the image in which I am finding it is imageBig . Now I am trying it using DFT to increase speed. I am following these steps as suggested by Cris Luengo Pad the template (floating image) to the size of the other image (with zeros). Compute the FFT of both. Flip the sign of the imaginary component of one of the results (complex

问题 I am trying to implement template matching using phase correlation. I have already done it in the spatial domain. You can see here My template image is imagePart and the image in which I am finding it is imageBig . Now I am trying it using DFT to increase speed. I am following these steps as suggested by Cris Luengo Pad the template (floating image) to the size of the other image (with zeros). Compute the FFT of both. Flip the sign of the imaginary component of one of the results (complex

问题 I'm trying to find multiple templates in an image using opencv python, according to this link. But the problem is that multiple points returned for a single object with a slightly difference in position. Something like this: I dont want to use cv2.minMaxLoc() because there is multiple templates in image. I wrote a function that delete the close positions, but I want to know is there any straightforward solution for this problem? thanks. 回答1: One way to find multiple matches is to write over