How can I perform the pattern matching process in SUB-IMAGE extracted from ORIGINAL-IMAGE and display the results in the original image

Question

For the whole day, I tried a lot to get all the associated matches (with the matchtemplate function) in the sub-Image, which is the ROI that I already extracted from the original image using the mousecallback function. So my code below is for Matchingfunction

////Matching Function void CTemplate_MatchDlg::OnBnTemplatematch() { namedWindow("reference",CV_WINDOW_AUTOSIZE); while(true) { Mat ref = imread("img.jpg"); // Original Image mod_ref = cvCreateMat(ref.rows,ref.cols,CV_32F);// resizing the image to fit in picture box resize(ref,mod_ref,Size(),0.5,0.5,CV_INTER_AREA); Mat tpl =imread("Template.jpg"); // TEMPLATE IMAGE cvSetMouseCallback("reference",find_mouseHandler,0); Mat aim=roiImg1.clone(); // SUB_IMAGE FROM ORIGINALIMAGE // aim variable contains the ROI matrix // next, want to perform template matching in that ROI // and display results on original image if(select_flag1 == 1) { // imshow("ref",aim); Mat res(aim.rows-tpl.rows+1, aim.cols-tpl.cols+1,CV_32FC1); matchTemplate(aim, tpl, res, CV_TM_CCOEFF_NORMED); threshold(res, res, 0.8, 1., CV_THRESH_TOZERO); while (1) { double minval, maxval, threshold = 0.8; Point minloc, maxloc; minMaxLoc(res, &minval, &maxval, &minloc, &maxloc); //// Draw Bound boxes for detected templates in sub matrix if (maxval >= threshold) { rectangle( aim, maxloc, Point(maxloc.x + tpl.cols, maxloc.y + tpl.rows), CV_RGB(0,255,0), 1,8,0 ); floodFill(res, maxloc, cv::Scalar(0), 0, cv::Scalar(.1), cv::Scalar(1.)); }else break; } } ////Bounding box for ROI selection with mouse rectangle(mod_ref, rect2, CV_RGB(255, 0, 0), 1, 8, 0); // rect2 is ROI // my idea is to get all the matches in ROI with bounding boxes // no need to mark any matches outside the ROI //Clearly i want to process only ROI imshow("reference", mod_ref); // show the image with the results waitKey(10); } //cvReleaseMat(&mod_ref); destroyWindow("reference"); } /// ImplementMouse Call Back void find_mouseHandler(int event, int x, int y, int flags, void* param) { if (event == CV_EVENT_LBUTTONDOWN && !drag) { /* left button clicked. ROI selection begins*/ point1 = Point(x, y); drag = 1; } if (event == CV_EVENT_MOUSEMOVE && drag) { /* mouse dragged. ROI being selected*/ Mat img3 = mod_ref.clone(); point2 = Point(x, y); rectangle(img3, point1, point2, CV_RGB(255, 0, 0), 1, 8, 0); imshow("reference", img3); // } if (event == CV_EVENT_LBUTTONUP && drag) { Mat img4=mod_ref.clone(); point2 = Point(x, y); rect1 = Rect(point1.x,point1.y,x-point1.x,y-point1.y); drag = 0; roiImg1 = mod_ref(rect1); //SUB_IMAGE MATRIX imshow("reference", img4); } if (event == CV_EVENT_LBUTTONUP) { /* ROI selected */ select_flag1 = 1; drag = 0; } } 

The build and debugging process completed successfully. But when I click the “Match” button in the dialog box, I get an error message:

 Unhandled exception at 0x74bf812f in Match.exe: Microsoft C++ exception: cv::Exception at memory location 0x001ae150.. 

So, my idea is to get all the matches in the Sub-image when comparing with TEMPLATE IMAGE and show the final result (matching with the bounding boxes) in the ORIGINAL IMAGE itself.

Someone help me in this regard! Help would be greatly appreciated.

Answer 1

My code below is a modification of the original tutorial provided by OpenCV.

It loads the image from the command line and displays it on the screen so that the user can draw a rectangle somewhere to select a sub-image that is a template. After this operation, the sub-image will be in a green rectangle :

Press any key for the program to perform pattern matching. A new window will appear called "Matching Pattern:" showing the original image as well as a blue rectangle which shows a matching area:

 #include <cv.h> #include <highgui.h> #include <iostream> const char* ref_window = "Draw rectangle to select template"; std::vector<cv::Point> rect_points; void mouse_callback(int event, int x, int y, int flags, void* param) { if (!param) return; cv::Mat* ref_img = (cv::Mat*) param; // Upon LMB click, store the X,Y coordinates to define a rectangle. // Later this info is used to set a ROI in the reference image. switch (event) { case CV_EVENT_LBUTTONDOWN: { if (rect_points.size() == 0) rect_points.push_back(cv::Point(x, y)); } break; case CV_EVENT_LBUTTONUP: { if (rect_points.size() == 1) rect_points.push_back(cv::Point(x, y)); } break; default: break; } if (rect_points.size() == 2) { cv::rectangle(*ref_img, rect_points[0], rect_points[1], cv::Scalar(0, 255, 0), 2); cv::imshow(ref_window, *ref_img); } } int main(int argc, char* argv[]) { if (argc < 2) { std::cout << "Usage: " << argv[0] << " <image>" << std::endl; return -1; } cv::Mat source = cv::imread(argv[1]); // original image if (source.empty()) { std::cout << "!!! Failed to load source image." << std::endl; return -1; } // For testing purposes, our template image will be a copy of the original. // Later we will present it in a window to the user, and he will select a region // as a template, and then we'll try to match that to the original image. cv::Mat reference = source.clone(); cv::namedWindow(ref_window, CV_WINDOW_AUTOSIZE); cv::setMouseCallback(ref_window, mouse_callback, (void*)&reference); cv::imshow(ref_window, reference); cv::waitKey(0); if (rect_points.size() != 2) { std::cout << "!!! Oops! You forgot to draw a rectangle." << std::endl; return -1; } // Create a cv::Rect with the dimensions of the selected area in the image cv::Rect template_roi = cv::boundingRect(rect_points); // Create THE TEMPLATE image using the ROI from the rectangle cv::Mat template_img = cv::Mat(source, template_roi); // Create the result matrix int result_cols = source.cols - template_img.cols + 1; int result_rows = source.rows - template_img.rows + 1; cv::Mat result; // Do the matching and normalize cv::matchTemplate(source, template_img, result, CV_TM_CCORR_NORMED); cv::normalize(result, result, 0, 1, cv::NORM_MINMAX, -1, cv::Mat()); /// Localizing the best match with minMaxLoc double min_val = 0, max_val = 0; cv::Point min_loc, max_loc, match_loc; int match_method = CV_TM_CCORR_NORMED; cv::minMaxLoc(result, &min_val, &max_val, &min_loc, &max_loc, cv::Mat()); // When using CV_TM_CCORR_NORMED, max_loc holds the point with maximum // correlation. match_loc = max_loc; // Draw a rectangle in the area that was matched cv:rectangle(source, match_loc, cv::Point(match_loc.x + template_img.cols , match_loc.y + template_img.rows), cv::Scalar(255, 0, 0), 2, 8, 0 ); imshow("Template Match:", source); cv::waitKey(0); return 0; }