[opencv]模板匹配算法（单图像模板匹配和基于模板匹配的目标跟踪）

1.模板匹配opencv函数

链接： http://www.opencv.org.cn/opencvdoc/2.3.2/html/modules/imgproc/doc/object_detection.html?highlight=matchtemplate#cv.MatchTemplate

matchTemplate ( InputArray  image , InputArray  temp , OutputArray  result , int  method )

Parameters:	image – Image where the search is running. It must be 8-bit or 32-bit floating-point. templ – Searched template. It must be not greater than the source image and have the same data type. result – Map of comparison results. It must be single-channel 32-bit floating-point. If image is and templ is  , then result is  . method – Parameter specifying the comparison method (see below).

第一个参数为输入源图像，第二个参数为输入模板图像，第三个参数为匹配结果，记录在源图像上滑动窗口和模板的相似程度，第四个参数为匹配方法。

匹配方法：

CV_TM_SQDIEF平方差匹配法,最好匹配为0，值越大匹配越差

CV_TM_SQDIEF_NORMED归一化平方差匹配法

CV_TM_CCORR相关匹配法，采用乘法操作，数值越大表明匹配越好

CV_TM_CCORR_NORMED归一化相关匹配法

CV_TM_CCOEFF相关系数匹配法，最好匹配为1，最差为-1

CV_TM_CCOEFF_NORMED归一化相关系数匹配法

各匹配方法原理见以上链接。

链接： http://www.opencv.org.cn/opencvdoc/2.3.2/html/modules/core/doc/operations_on_arrays.html?highlight=minmaxloc#cv.MinMaxLoc

minMaxLoc ( InputArray  src , double*  minVal , double*  maxVal =0, Point*  minLoc =0, Point*  maxLoc =0, InputArray mask =noArray() )

Parameters:

src – Source single-channel array. minVal – Pointer to the returned minimum value. NULL is used if not required. maxVal – Pointer to the returned maximum value. NULL is used if not required. minLoc – Pointer to the returned minimum location (in 2D case). NULL is used if not required. maxLoc – Pointer to the returned maximum location (in 2D case). NULL is used if not required. mask – Optional mask used to select a sub-array.

寻找矩阵中最大最小值以及对应坐标。

2.单图像模板匹配

原图：

模板图像：

代码如下：

#include "stdafx.h"
#include "cv.h"
#include "highgui.h"
#include "cxcore.h"

using namespace std;
using namespace cv;

int _tmain(int argc, _TCHAR* argv[])
{
	Mat img,templ,result;
	img = imread("1.jpg");
	templ = imread("2.jpg");

	int result_cols = img.cols - templ.cols + 1;
	int result_rows = img.rows - templ.rows + 1;
	result.create(result_cols, result_rows, CV_32FC1);

	matchTemplate(img, templ, result, CV_TM_SQDIFF_NORMED);//CV_TM_SQDIFF_NORMED CV_TM_SQDIFF
	normalize(result, result, 0, 1, NORM_MINMAX, -1, Mat());

	double minVal;
	double maxVal;
	Point minLoc;
	Point maxLoc;
	Point matchLoc;

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

	matchLoc = minLoc;

	rectangle(img, matchLoc, Point(matchLoc.x + templ.cols, matchLoc.y + templ.rows), Scalar(0,255,0), 2, 8, 0);

	imshow("img", img);
	waitKey(0);

	return 0;
}

效果如下：

3.基于模板匹配的目标跟踪

由于采用鼠标画矩形框的方式进行模板图像的提取，所以对鼠标响应函数进行说明。

cvSetMouseCallback ( const char*  name , CvMouseCallback  onMouse , void*  param =NULL  )

Parameters:	name – Window name onMouse – Mouse callback. See OpenCV samples, such ashttps://code.ros.org/svn/opencv/trunk/opencv/samples/cpp/ffilldemo.cpp, on how to specify and use the callback. param – The optional parameter passed to the callback.

第一个参数为使用窗口名，第二个为onMouse鼠标消息消息处理函数，第三个为传给鼠标消息的任定参数。

这里添加onMouse函数如下：

void onMouse(int event,int x,int y,int flags,void*param)//事件回传代号，坐标，代号，Mouse事件的代号名称
{
	if (pause)
	{
		switch (event)
		{
		case CV_EVENT_MOUSEMOVE:
			if (drawbox){
				box.width = x - box.x;
				box.height = y - box.y;
			}
			break;
		case CV_EVENT_LBUTTONDOWN:
			drawbox = true;
			box = Rect(x, y, 0, 0);
			break;
		case CV_EVENT_LBUTTONUP:
			drawbox = false;
			if (box.width < 0){
				box.x += box.width;
				box.width *= -1;
			}
			if (box.height < 0){
				box.y += box.height;
				box.height *= -1;
			}

			cvtColor(img,imggray,CV_RGB2GRAY);
			templ = imggray(box);
			tracking = true;	
			rectangle(frame, box, Scalar(0, 255, 0), 3);
			imshow("ORI", frame);	
			imshow("Templ", templ);

			break;
		}
	}
}

Event:

 #define CV_EVENT_MOUSEMOVE 0                    滑動 

#define CV_EVENT_LBUTTONDOWN 1              左鍵點擊 

#define CV_EVENT_RBUTTONDOWN 2             右鍵點擊

 #define CV_EVENT_MBUTTONDOWN 3            中鍵點擊 

#define CV_EVENT_LBUTTONUP 4                     左鍵放開 

#define CV_EVENT_RBUTTONUP 5                    右鍵放開 

#define CV_EVENT_MBUTTONUP 6                    中鍵放開 

#define CV_EVENT_LBUTTONDBLCLK 7           左鍵雙擊

 #define CV_EVENT_RBUTTONDBLCLK 8         右鍵雙擊

 #define CV_EVENT_MBUTTONDBLCLK 9         中鍵雙擊

flags: 
#define CV_EVENT_FLAG_LBUTTON 1             左鍵拖曳

 #define CV_EVENT_FLAG_RBUTTON 2           右鍵拖曳

 #define CV_EVENT_FLAG_MBUTTON 4           中鍵拖曳 

#define CV_EVENT_FLAG_CTRLKEY 8            (8~15)按Ctrl不放事件

 #define CV_EVENT_FLAG_SHIFTKEY 16        (16~31)按Shift不放事件

 #define CV_EVENT_FLAG_ALTKEY 32            (32~39)按Alt不放事件

模板匹配跟踪函数如下：

void track(Mat gray, Mat &templ, Rect &box)
{
	double minVal;
	double maxVal;
	Point minLoc;
	Point maxLoc;
	matchTemplate(gray, templ, result, CV_TM_SQDIFF);
	minMaxLoc(result, &minVal, &maxVal, &minLoc, &maxLoc, Mat());
	matchLoc = minLoc;
	rectangle(gray, matchLoc, Point(matchLoc.x + templ.cols, matchLoc.y + templ.rows), Scalar(0,0,255), 2, 8, 0);
}

GIF效果如下：