自学教程：如何基于opencv实现简单的数字识别

#include <opencv2/core/core.hpp>#include <opencv.hpp>#include <opencv2/highgui/highgui.hpp>#include <opencv2/features2d/features2d.hpp>#include <opencv2/imgproc/imgproc.hpp>#include <iostream>#include <ctime>using namespace std ;using namespace cv;#include <map>Mat src_threshold;Mat src_dil;int sunImage(Mat &image);vector<Mat>ROI_image;//待测图片int main() {	clock_t start ,finish;	start=clock();	Mat src;	src=imread("D://vspic//picture//number6.jpg");	resize(src,src,Size(src.cols/7,src.rows/7));	imshow("src",src);	Mat src_gray;	cvtColor(src,src_gray,COLOR_BGR2GRAY);	//imshow("gsrc_ray",src_gray);	Mat src_blur;	blur(src_gray,src_blur,Size(9,9));	//GaussianBlur(src_gray,src_blur,Size(11,11),1,1);	Mat src_threshold;	threshold(src_blur,src_threshold,150,255,THRESH_OTSU);	//imshow("src_threshold",src_threshold);	Mat src_canny;	Canny(src_threshold,src_canny,125,255,3);	//imshow("src_canny",src_canny);	vector<vector<Point>>contours_src;	vector<Vec4i>hierarchy_src(contours_src.size());	findContours(src_canny,contours_src,hierarchy_src,RETR_EXTERNAL,CHAIN_APPROX_NONE);	Rect rect_s;	Rect choose_rect;	for (size_t i=0;i<contours_src.size();i++)	{		rect_s=boundingRect(contours_src[i]);		double width=rect_s.width;		double height= rect_s.height;		double bizhi=width/height;		if (bizhi>1.5&&height>50)		{			/*rectangle(src,rect_s.tl(),rect_s.br(),Scalar(255,255,255),1,1,0);*/			choose_rect=Rect(rect_s.x+20,rect_s.y+30,rect_s.x-30,rect_s.y-108);		}	}	Mat roi;	roi=src(choose_rect);	//imshow("src_",roi);	Mat img =roi;	Mat gray_img;	// 生成灰度图像	cvtColor(img, gray_img, CV_BGR2GRAY);	// 高斯模糊	Mat img_gau;	GaussianBlur(gray_img, img_gau, Size(3, 3), 0, 0);	// 阈值分割	Mat img_seg;	threshold(img_gau, img_seg, 0, 255, THRESH_BINARY + THRESH_OTSU);	Mat element;	element=getStructuringElement(MORPH_RECT,Size(8,8));	erode(img_seg,src_dil,element);	//imshow("src_dil",src_dil);	// 边缘检测，提取轮廓	Mat img_canny;	Canny(src_dil, img_canny, 200, 100);	//imshow("canny",img_canny);	vector<vector<Point>> contours;	vector<Vec4i> hierarchy(contours.size());	findContours(img_canny, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE, Point());//寻找轮廓	int size = (int)(contours.size());//轮廓的数量	//cout<<size<<endl;6个	// 保存符号边框的序号	vector<int> num_order;//定义一个整型int容器	map<int, int> num_map;//容器，需要关键字和模板对象两个模板参数，此处定义一个int作为索引，并拥有相关连的指向int的指针	for (int i = 0; i < size; i++)   {		// 获取边框数据		Rect number_rect = boundingRect(contours[i]);		int width = number_rect.width;//获取矩形的宽		int height = number_rect.height;//获取矩形的高		// 去除较小的干扰边框，筛选出合适的区域		if (width > img.cols/20 )		{			rectangle(img,number_rect.tl(),number_rect.br(),Scalar(255,255,255),1,1,0);//绘制矩形			imshow("img",img);//显示矩形框			num_order.push_back(number_rect.x);//把矩形的x坐标放入number_order容器中，将一个新的元素添加到vector的最后面，			//位置为当前元素的下一个元素			num_map[number_rect.x] = i;//向map中存入键值对，number_rect.x是关键字，i是值			/*把矩形框的x坐标与对应的i值一起放入map容器中，形成一一对应的键值对			*/		}	}	// 按符号顺序提取	sort(num_order.begin(), num_order.end());/*把number_order容器中的内容按照从小到大的顺序排列,这里面是X的坐标*/	for (int i = 0; i < num_order.size(); i++) {		Rect number_rect = boundingRect(contours[num_map.find(num_order[i])->second]);//num_order里面放的是坐标		//cout<<"num_map的值是："<<num_map.find(num_order[i])->second<<endl;		Rect choose_rect(number_rect.x, 0, number_rect.width, img.rows);//矩形左上角x,y的坐标以及矩形的宽和高		Mat number_img = img(choose_rect);		resize(number_img,number_img,Size(30,100));//归一化尺寸		ROI_image.push_back(number_img);//保存为待测图片		//imshow("number" + to_string(i), number_img);		char name[50];		sprintf_s(name,"D://vs2012//model//%d.jpg",i);//保存模板		imwrite(name, number_img);		}	cout<<"图片分割完毕"<<endl;	//加载模板	vector<Mat>temptImage;//存放模板	for (int i=0;i<4;i++)	{		char name[50];		sprintf_s(name,"D://vs2012//model//%d.jpg",i);		Mat temp;		temp=imread(name);		//cout<<"加载模板图片通道数："<<temp.channels()<<endl;		temptImage.push_back(temp);	}	vector<int>seq;//存放顺序结果	for (int i=0;i<ROI_image.size();i++)	{		Mat subImage;		int sum=0;		int min=50000;		int seq_min=0;//记录最小的和对应的数字		for (int j=0;j<4;j++)		{			absdiff(ROI_image[i],temptImage[j],subImage);//待测图片像素减去模板图片像素			sum=sunImage(subImage);//统计像素和			if (sum<min)			{				min=sum;			    seq_min=j;			}			sum=0;		}		seq.push_back(seq_min);	}	cout<<"输出数字匹配结果:";//endl是换行的意思	for (int i=0;i<seq.size();i++)//输出结果，小数点固定在第3位	{		cout<<seq[i];		if (i==1)		{			cout<<".";		}	}	finish=clock();	double all_time=double(finish-start)/CLOCKS_PER_SEC;	/*cout<<"运行总时间是："<<all_time<<endl;*/	waitKey(0);	return 0;}//计算像素和int sunImage(Mat &image){	int sum=0;	for (int i=0;i<image.cols;i++)	{		for (int j=0;j<image.rows;j++)		{			sum+=image.at<uchar>(j,i);		}	}	return sum;}