c++ - 如何在从原始图像中提取的子图像中执行模板匹配过程并在原始图像中显示结果

Question

一整天，我尝试了很多次来获取 sub-Image 中的所有相关匹配项(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用于匹配功能

 ////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，当我在对话框中单击“匹配”按钮时，出现错误:

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模板图像进行比较时获取子图像中的所有匹配项，并在原始图像本身中显示最终结果(与边界框匹配)。

任何人在这方面帮助我!!帮助将不胜感激!!

Answer 1

我下面的代码是对 original tutorial 的修改由 OpenCV 提供。

它从命令行加载图像并将其显示在屏幕上，这样用户可以在某处画一个矩形来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:

按任意键让程序进行模板匹配。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一个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;
}