#include "opencv2/highgui/highgui.hpp"  
#include "opencv2/imgproc/imgproc.hpp"  
using namespace cv;  
  
  
//-----------------------------------【宏定义部分】--------------------------------------------   
//  描述：定义一些辅助宏   
//------------------------------------------------------------------------------------------------   
#define WINDOW_NAME1 "【原始图片】"        //为窗口标题定义的宏   
#define WINDOW_NAME2 "【匹配窗口】"        //为窗口标题定义的宏   
  
//-----------------------------------【全局变量声明部分】------------------------------------  
//          描述：全局变量的声明  
//-----------------------------------------------------------------------------------------------  
Mat g_srcImage; Mat g_templateImage; Mat g_resultImage;  
int g_nMatchMethod;  
int g_nMaxTrackbarNum = 5;  
  
//-----------------------------------【全局函数声明部分】--------------------------------------  
//          描述：全局函数的声明  
//-----------------------------------------------------------------------------------------------  
void on_Matching( int, void* );  
static void ShowHelpText( );  
  
  
//-----------------------------------【main( )函数】--------------------------------------------  
//          描述：控制台应用程序的入口函数，我们的程序从这里开始执行  
//-----------------------------------------------------------------------------------------------  
int main(  )  
{  
    //【0】改变console字体颜色  
    system("color 1F");   
  
    //【0】显示帮助文字  
    ShowHelpText();  
  
    //【1】载入原图像和模板块  
    g_srcImage = imread( "1.jpg", 1 );  
    g_templateImage = imread( "2.jpg", 1 );  
  
    //【2】创建窗口  
    namedWindow( WINDOW_NAME1, CV_WINDOW_AUTOSIZE );  
    namedWindow( WINDOW_NAME2, CV_WINDOW_AUTOSIZE );  
  
    //【3】创建滑动条并进行一次初始化  
    createTrackbar( "方法", WINDOW_NAME1, &g_nMatchMethod, g_nMaxTrackbarNum, on_Matching );  
    on_Matching( 0, 0 );  
  
    waitKey(0);  
    return 0;  
  
}  
  
//-----------------------------------【on_Matching( )函数】--------------------------------  
//          描述：回调函数  
//-------------------------------------------------------------------------------------------  
void on_Matching( int, void* )  
{  
    //【1】给局部变量初始化  
    Mat srcImage;  
    g_srcImage.copyTo( srcImage );  
  
    //【2】初始化用于结果输出的矩阵  
    int resultImage_cols =  g_srcImage.cols - g_templateImage.cols + 1;  
    int resultImage_rows = g_srcImage.rows - g_templateImage.rows + 1;  
    g_resultImage.create( resultImage_cols, resultImage_rows, CV_32FC1 );  
  
    //【3】进行匹配和标准化  
    matchTemplate( g_srcImage, g_templateImage, g_resultImage, g_nMatchMethod );  
    normalize( g_resultImage, g_resultImage, 0, 1, NORM_MINMAX, -1, Mat() );  
  
    //【4】通过函数 minMaxLoc 定位最匹配的位置  
    double minValue; double maxValue; Point minLocation; Point maxLocation;  
    Point matchLocation;  
    minMaxLoc( g_resultImage, &minValue, &maxValue, &minLocation, &maxLocation, Mat() );  
  
    //【5】对于方法 SQDIFF 和 SQDIFF_NORMED, 越小的数值有着更高的匹配结果. 而其余的方法, 数值越大匹配效果越好  
    if( g_nMatchMethod  == CV_TM_SQDIFF || g_nMatchMethod == CV_TM_SQDIFF_NORMED )  
    { matchLocation = minLocation; }  
    else  
    { matchLocation = maxLocation; }  
  
    //【6】绘制出矩形，并显示最终结果  
    rectangle( srcImage, matchLocation, Point( matchLocation.x + g_templateImage.cols , matchLocation.y + g_templateImage.rows ), Scalar(0,0,255), 2, 8, 0 );  
    rectangle( g_resultImage, matchLocation, Point( matchLocation.x + g_templateImage.cols , matchLocation.y + g_templateImage.rows ), Scalar(0,0,255), 2, 8, 0 );  
  
    imshow( WINDOW_NAME1, srcImage );  
    imshow( WINDOW_NAME2, g_resultImage );  
  
}  
  
  
  
static void ShowHelpText()  
{  
      
    //输出一些帮助信息  
    printf("\t欢迎来到【模板匹配】示例程序~\n");   
    printf("\n\n\t请调整滑动条观察图像效果\n\n");  
    printf(  "\n\t滑动条对应的方法数值说明: \n\n"   
        "\t\t方法【0】- 平方差匹配法(SQDIFF)\n"   
        "\t\t方法【1】- 归一化平方差匹配法(SQDIFF NORMED)\n"   
        "\t\t方法【2】- 相关匹配法(TM CCORR)\n"   
        "\t\t方法【3】- 归一化相关匹配法(TM CCORR NORMED)\n"   
        "\t\t方法【4】- 相关系数匹配法(TM COEFF)\n"   
        "\t\t方法【5】- 归一化相关系数匹配法(TM COEFF NORMED)\n" );    
}  

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