opencv教程中的代碼

/*

對1280*1280的圖片配對32*32的模板，耗時在300ms左右
該方法對32*32的圖像應與1280*1280的一部分完全相同，該配對才會準確
*/


#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>


using namespace std;
using namespace cv;


/// Global Variables
Mat img; Mat templ; Mat result;
char* image_window = "Source Image";
char* result_window = "Result window";


int match_method;
int max_Trackbar = 5;


/// Function Headers
void MatchingMethod(int, void*);


/** @function main */
int main(int argc, char** argv)
{
/// Load image and template
img = imread("1.jpg", 1);//1為大圖片
templ = imread("2.jpg", 1);//2為小圖片


/// Create windows
namedWindow(image_window, CV_WINDOW_AUTOSIZE);
namedWindow(result_window, CV_WINDOW_AUTOSIZE);


/// Create Trackbar
char* trackbar_label = "Method: \n 0: SQDIFF \n 1: SQDIFF NORMED \n 2: TM CCORR \n 3: TM CCORR NORMED \n 4: TM COEFF \n 5: TM COEFF NORMED";
createTrackbar(trackbar_label, image_window, &match_method, max_Trackbar, MatchingMethod);


MatchingMethod(0, 0);


waitKey(0);
return 0;
}


/**
* @function MatchingMethod
* @brief Trackbar callback
*/
void MatchingMethod(int, void*)
{
double tick = (double)getTickCount();
/// Source image to display
Mat img_display;
img.copyTo(img_display);


/// Create the result matrix
int result_cols = img.cols - templ.cols + 1;
int result_rows = img.rows - templ.rows + 1;


result.create(result_rows, result_cols, CV_32FC1);


/// Do the Matching and Normalize
matchTemplate(img, templ, result, match_method);
normalize(result, result, 0, 1, NORM_MINMAX, -1, Mat());


/// Localizing the best match with minMaxLoc
double minVal; double maxVal; Point minLoc; Point maxLoc;
Point matchLoc;


minMaxLoc(result, &minVal, &maxVal, &minLoc, &maxLoc, Mat());


/// For SQDIFF and SQDIFF_NORMED, the best matches are lower values. For all the other methods, the higher the better
if (match_method == CV_TM_SQDIFF || match_method == CV_TM_SQDIFF_NORMED)
{
matchLoc = minLoc;
}
else
{
matchLoc = maxLoc;
}


/// Show me what you got
rectangle(img_display, matchLoc, Point(matchLoc.x + templ.cols, matchLoc.y + templ.rows), Scalar::all(0), 2, 8, 0);
rectangle(result, matchLoc, Point(matchLoc.x + templ.cols, matchLoc.y + templ.rows), Scalar::all(0), 2, 8, 0);


imshow(image_window, img_display);
imshow(result_window, result);
cout << "Recv: " << 1000 * ((double)getTickCount() - tick) / getTickFrequency() << endl;
return;

}

圖片效果：

總結

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