步驟:

1.影象分割->製作模板;

2.目標圖片分割->比對識別;

#include <stdio.h>
#include <stdlib.h>
#include <opencv\cv.hpp>
#include <opencv2\opencv.hpp>
#include <iostream>
#include <fstream>
#include <Windows.h>
using namespace cv;
using namespace std;

int getColSum(Mat src,int col)
{
	int sum = 0;
	int height = src.rows;
	int width = src.cols;
	for (int i = 0; i < height; i++)
	{
		sum = sum + src.at <uchar>(i, col);
	}
	return sum;
}

int getRowSum(Mat src, int row)
{
	int sum = 0;
	int height = src.rows;
	int width = src.cols;
	for (int i = 0; i < width; i++)
	{
		sum += src.at <uchar>(row, i);
	}
	return sum;
}


void cutTop(Mat& src, Mat& dstImg)//上下切割
{
	int top, bottom;
	top = 0;
	bottom = src.rows;

	int i;
	for (i = 0; i < src.rows; i++)
	{
		int colValue = getRowSum(src, i);
		//cout <<i<<" th "<< colValue << endl;
		if (colValue>0)
		{
			top = i;
			break;
		}
	}
	for (; i < src.rows; i++)
	{
		int colValue = getRowSum(src, i);
		//cout << i << " th " << colValue << endl;
		if (colValue == 0)
		{
			bottom = i;
			break;
		}
	}

	int height = bottom - top;
	Rect rect(0, top, src.cols, height);
	dstImg = src(rect).clone();
}

int cutLeft(Mat& src, Mat& leftImg, Mat& rightImg)//左右切割
{
	int left, right;
	left = 0;
	right = src.cols;

	int i;
	for (i = 0; i < src.cols; i++)
	{
		int colValue = getColSum(src, i);
		//cout <<i<<" th "<< colValue << endl;
		if (colValue>0)
		{
			left = i;
			break;
		}
	}
	if (left == 0)
	{
		return 1;
	}


	for (; i < src.cols; i++)
	{
		int colValue = getColSum(src, i);
		//cout << i << " th " << colValue << endl;
		if (colValue == 0)
		{
			right = i;
			break;
		}
	}
	int width = right - left;
	Rect rect(left, 0, width, src.rows);
	leftImg = src(rect).clone();
	Rect rectRight(right, 0, src.cols - right, src.rows);
	rightImg = src(rectRight).clone();
	cutTop(leftImg, leftImg);
	return 0;
}


void getPXSum(Mat &src, int &a)//獲取所有畫素點和
{ 
	threshold(src, src, 100, 255, CV_THRESH_BINARY);
	  a = 0;
	for (int i = 0; i < src.rows;i++)
	{
		for (int j = 0; j < src.cols; j++)
		{
			a += src.at <uchar>(i, j);
		}
	}
}

int  getSubtract(Mat &src, int TemplateNum) //兩張圖片相減
{
	Mat img_result;
	int min = 10000000;
	int serieNum = 0;
	for (int i = 0; i < TemplateNum; i++){
		char name[20];
		sprintf_s(name, "D:\\%dLeft.jpg", i);
		Mat Template = imread(name, CV_LOAD_IMAGE_GRAYSCALE);
		threshold(Template, Template, 200, 255, CV_THRESH_BINARY);
		threshold(src, src, 80, 255, CV_THRESH_BINARY);
		resize(src, src, Size(32, 48), 0, 0, CV_INTER_LINEAR);
		resize(Template, Template, Size(32, 48), 0, 0, CV_INTER_LINEAR);
		//imshow(name, Template);
		absdiff(Template, src, img_result);
		int diff = 0;
		getPXSum(img_result, diff);
		if (diff < min)
		{
			min = diff;
			serieNum = i;
		}
	}
	if(serieNum!=10)
	{
		/*
	printf("最小距離是%d ", min);
	printf("匹配到第%d個模板匹配的數字是%d\n", serieNum,serieNum);*/
	cout<<serieNum;
	}
	return serieNum;
}




	

int main()
{

	clock_t startTime,mattime,endTime;  
    startTime = clock(); 
	 RECT rc;
   HWND hwnd = FindWindow(NULL,TEXT("開獎資料-北京時時彩")); //注意視窗不能最小化 
   if (hwnd == NULL)
   { 
      cout << "找不到視窗" << endl;
      return 0;
   }
   GetClientRect(hwnd, &rc);
 
  //建立空點陣圖
   HDC hdcScreen = GetDC(NULL);
   HDC hdc = CreateCompatibleDC(hdcScreen);
   HBITMAP hbmp = CreateCompatibleBitmap(hdcScreen, rc.right - rc.left, rc.bottom - rc.top);  
   SelectObject(hdc, hbmp); 
   //得到目標視窗點陣圖
   PrintWindow(hwnd, hdc, PW_CLIENTONLY);
   BITMAP bm;//影象資訊;
   GetObject(hbmp, sizeof(bm), (LPSTR)&bm);
   //把bmp影象轉為Mat型別進行opencv的函式操作;
    Mat dst;
	dst.create(cvSize(bm.bmWidth,bm.bmHeight),CV_8UC4);
	GetBitmapBits(hbmp,bm.bmWidth*bm.bmHeight*4,dst.data);
    cvtColor(dst,dst,CV_BGRA2BGR);   
	imshow("cap",dst);
	//釋放dc
   DeleteDC(hdc); 
   DeleteObject(hbmp); 
   ReleaseDC(NULL, hdcScreen); 

     cout<<"開獎資料識別結果:"<<endl;
	 int roiheight=bm.bmHeight-125;
	 for(int k=0;k<roiheight/33;k++)//roiheight/33
	 {
		 mattime=clock();
	 Rect re(210,125+k*33,100,30);
	 Mat src(dst,re);
	 imshow("roi",src);
	 cvtColor(src,src,CV_BGR2GRAY); 
	//Mat src = imread("D:\\1.bmp", CV_LOAD_IMAGE_GRAYSCALE);
	threshold(src, src, 100 , 255, CV_THRESH_BINARY);
	//adaptiveThreshold(src, src, 255, CV_ADAPTIVE_THRESH_MEAN_C, CV_THRESH_BINARY_INV, 31,0);
	bitwise_not(src,src);
	imshow("origin", src);
	//imwrite("d:\\sa.bmp",src);
	
	Mat leftImg,rightImg;
	int res = cutLeft(src, leftImg, rightImg);
	int i = 0; 
	while (res == 0)
	{ 		
		//製作樣本//
		/*
		char nameLeft[10];
		sprintf(nameLeft, "%dLeft", i);
		char nameRight[10];
		sprintf(nameRight, "%dRight", i);
		i++;
		imshow(nameLeft, leftImg);
		stringstream ss;
		ss << nameLeft;
		imwrite("D:\\" + ss.str() + ".jpg", leftImg);
		ss >> nameLeft;*/
		//檢測//
		Mat srcTmp = rightImg;
		getSubtract(leftImg, 11);
		res = cutLeft(srcTmp, leftImg, rightImg);	
	}
	cout<<endl;
	 }
	 endTime = clock();  
	 cout<<"影象處理時間"<<(double)(mattime - startTime) / CLOCKS_PER_SEC<<"s"<<endl;
    cout << "Totle Time : " <<(double)(endTime - startTime) / CLOCKS_PER_SEC << "s" << endl; 
	waitKey(0);
	return 0;
}