如何在从ORIGINAL-IMAGE中提取的SUB-IMAGE中执行模板匹配过程并在原始图像中显示结果

Question

整整一天我已经尝试了很多东西来获得子图像中的所有相关匹配（使用matchtemplate函数），这是我已经使用mousecallback函数从原始图像中提取的ROI。 所以我的代码在下面是匹配功能

 ////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;
}
}

构建和调试过程成功完成。 但是，当我单击对话框中的匹配按钮时，我收到错误：

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

所以我的想法是在与TEMPLATE IMAGE比较时获取子图像中的所有匹配，并在原始图像本身中显示最终结果（与边界框匹配）。

在这方面有人帮助我！ 帮助将非常感激!!

Answer 1

我的下面的代码是对OpenCV提供的原始教程的修改 。

它从命令行加载图像并将其显示在屏幕上，以便用户可以在某处绘制矩形以选择子图像作为模板。 完成该操作后，子图像将位于绿色矩形内 ：

按任意键让程序执行模板匹配。 将出现一个标题为“ 模板匹配： ”的新窗口，其中显示原始图像以及显示匹配区域的蓝色矩形 ：

#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;
}