opencv检查pin脚长度

其他 2019-01-05 09:31:09 阅读次数: 0 
#include<iostream>

#include <opencv2/opencv.hpp>


using namespace std;
using namespace cv;

int main()
{
	Mat src = imread("F:\\PIN_LENGTH\\3.bmp");
	
	Mat dst = Mat::zeros(src.size(), src.type());
	
	//点
	Mat ROI_src_point = src(Range(1650,1750), Range(650,1650));		//ROI端点
	Mat ROI_src_point_gray;											
	cvtColor(ROI_src_point, ROI_src_point_gray, COLOR_BGR2GRAY, 1);  //ROI端点的灰度图
	ROI_src_point_gray = ROI_src_point_gray > 150;                   //阀值二值化
	//线
	Mat ROI_src_line = src(Range(1400, 1450), Range(650, 1650));    //ROI直线
	Mat ROI_src_line_gray;
	cvtColor(ROI_src_line, ROI_src_line_gray, COLOR_BGR2GRAY, 1);  //ROI直线的灰度图
	ROI_src_line_gray = ROI_src_line_gray > 150;                   //阀值二值化


	//**********************************【找出点所在轮廓】**********************************************
	vector<vector<Point>> contours;
	vector<Vec4i> hierarchy;
	findContours(ROI_src_point_gray, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE);
	//用最小矩形包围轮廓
	vector<Rect> boundRect( contours.size() );
	
	for( int i = 0; i < contours.size(); i++ )
	{
		boundRect[i] = boundingRect( Mat(contours[i]) );
	}
	vector<Point> pin_point;

	//筛选出符合要求的矩形， 并计算出尖点
	for( int i = 0; i< boundRect.size(); i++ )
	{	
		if(boundRect[i].br().y - boundRect[i].tl().y > 20)	
		{
			rectangle( ROI_src_point, boundRect[i].tl(), boundRect[i].br(), Scalar(0,0,255), 2, 8, 0 );
			
			float aa = boundRect[i].br().x - (boundRect[i].br().x - boundRect[i].tl().x) / 2.0;
			float bb = boundRect[i].br().y;
			Point p = Point(aa,bb);
			pin_point.push_back(p);

		}
	}
	
	//对尖点进行排序（轮廓选举出的为逆排序，我不知道其他情况轮廓的产生顺序， 最好进行一下排序）
	vector<Point> xx;
	vector<Point>::reverse_iterator it;
	for(it = pin_point.rbegin(); it != pin_point.rend(); it++)
	{
		xx.push_back(*it);
	}
	//冒泡排序
	for (int i = 0; i < xx.size() - 1; i++)
	{
		for(int j = i + 1; j < xx.size(); j++)
		{
			if(xx[i].x > xx[j].x)
			{
				Point p;
				p = xx[i];
				xx[i] = xx[j];
				xx[j] = p;
				cout << endl<< p << endl;
			}

		}
	}
	
	for(int i = 0; i < xx.size(); i ++)             //最终xx为需要的点集
	{
		xx[i].x += 650;
		xx[i].y += 1650;
	}
	for(int i = 0; i < xx.size(); i++)                            
	{
		circle(src, xx[i], 30,Scalar(0,0,255),0);
		circle(src, xx[i],2,Scalar(0,255,0),-1);
	}

//************************************【找出线的点集】********************************************************
	vector<vector<Point>> contours_line;
	vector<Vec4i> hierarchy_line;
	findContours(ROI_src_line_gray, contours_line, hierarchy_line, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE);
	//用最小矩形包围轮廓
	vector<Rect> boundRect_line( contours_line.size() );
	
	for( int i = 0; i < contours_line.size(); i++ )
	{
		boundRect_line[i] = boundingRect( Mat(contours_line[i]) );
	}

	vector<Point> line_point;
	//筛选出符合要求的矩形， 并计算出尖点
	for( int i = 0; i< boundRect_line.size(); i++ )
	{	
		if(boundRect_line[i].br().y == 49 && boundRect_line[i].br().x - boundRect_line[i].tl().x > 10)						//筛选条件(49为1450-1400 从0开始的)	
		{
			rectangle( ROI_src_line, boundRect_line[i].tl(), boundRect_line[i].br(), Scalar(0,0,255), 2, 8, 0 );
			cout << boundRect_line[i].tl() << " " << boundRect_line[i].br() << endl;
			float aa = boundRect_line[i].br().x;
			float bb = boundRect_line[i].tl().y;
			Point p = Point(aa,bb);
			line_point.push_back(boundRect_line[i].tl());
			line_point.push_back(p);

			cout << p << endl;
		}
	}

	for(int i = 0; i < line_point.size(); i ++)             //最终line_point为需要的点集
	{
		line_point[i].x += 650;
		line_point[i].y += 1400;
	}
	for(int i = 0; i < line_point.size(); i++)                            
	{
		circle(src, line_point[i], 10,Scalar(0,0,255),0);
		circle(src, line_point[i],2,Scalar(0,255,0),-1);
	}

	//拟合直线
	Vec4f line_para;   
	cv::fitLine(line_point, line_para, CV_DIST_L2, 0, 0.01, 0.01);
	cout << endl<<line_para;

	//获取点斜式的点和斜率
	cv::Point point0;
	point0.x = line_para[2];
	point0.y = line_para[3];

	double k = line_para[1] / line_para[0];

	//计算直线的端点(y = k(x - x0) + y0)
	cv::Point point1, point2;
	point1.x = 0;
	point1.y = k * (0 - point0.x) + point0.y;
	point2.x = src.cols-100;
	point2.y = k * (src.cols-100 - point0.x) + point0.y;

	cv::line(src, point1,point2, cv::Scalar(255,0,0), 1, 8, 0);          //画出这条线

	//********************************************【求出端点到直线的距离】**************************************
	vector<double> solution;
	double A = point1.y - point2.y;
	double B = point2.x - point1.x;
	double C = point1.x * point2.y - point2.x * point1.y;

		cout <<"***********************"<<endl;
	for(int i = 0; i < xx.size(); i++)
	{
		double b = fabs(A * xx[i].x + B * xx[i].y + C);
		double n = b / sqrt(A * A + B * B);
		solution.push_back(n);
		cout << n << endl;
		string s = to_string(n);
		putText(src, s,xx[i],FONT_HERSHEY_SIMPLEX,0.5,Scalar(150,150,0),2,8);   //把数值写在旁边
	}

	




	namedWindow("nn", WINDOW_NORMAL);
	imshow("nn",src);
	imshow("over", ROI_src_point);
	imshow("hh", ROI_src_line);
	waitKey(0);
}

下面这个是用canny检测， 而不是阈值， 但是是像素精度， 需要把它改成亚像素精度， 这样就要看opencv源代码了。

比如boundingrect() 如何输出亚像素精度坐标， 以及我用到的其他函数， 边缘检测， 都需要修改。

#include<iostream>

#include <opencv2/opencv.hpp>


using namespace std;
using namespace cv;

int main()
{
	Mat src = imread("F:\\PIN_LENGTH\\9.bmp");
	
	Mat dst = Mat::zeros(src.size(), src.type());
	
	//点
	Mat ROI_src_point = src(Range(1650,1750), Range(650,1650));		//ROI端点
	Mat ROI_src_point_;											
	cvtColor(ROI_src_point, ROI_src_point_, COLOR_BGR2GRAY, 1);  //ROI端点的灰度图
	Mat ROI_src_point_gray;											//canny检测, 用双边滤波（保边）
	bilateralFilter(ROI_src_point_, ROI_src_point_gray, 10, 15, 5);
	Canny(ROI_src_point_gray, ROI_src_point_gray, 100, 200, 3, true);
	//线
	Mat ROI_src_line = src(Range(1400, 1450), Range(650, 1650));    //ROI直线
	Mat ROI_src_line_ ;
	Mat ROI_src_line_gray;
	cvtColor(ROI_src_line, ROI_src_line_ , COLOR_BGR2GRAY, 1);  //ROI直线的灰度图
	bilateralFilter(ROI_src_line_, ROI_src_line_gray, 10, 15, 5);            //双边滤波， canny检测
	Canny(ROI_src_line_gray, ROI_src_line_gray, 100, 200, 3, true);


	//**********************************【找出点所在轮廓】**********************************************
	vector<vector<Point>> contours;
	vector<Vec4i> hierarchy;
	findContours(ROI_src_point_gray, contours, hierarchy, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);
	//用最小矩形包围轮廓
	vector<Rect> boundRect( contours.size() );
	
	for(unsigned int i = 0; i < contours.size(); i++ )
	{
		boundRect[i] = boundingRect( Mat(contours[i]) );
	}
	vector<Point> pin_point;

	//筛选出符合要求的矩形， 并计算出尖点
	for(unsigned int i = 0; i< boundRect.size(); i++ )
	{	
		if(boundRect[i].br().y - boundRect[i].tl().y > 10 && boundRect[i].br().x - boundRect[i].tl().x > 13 && boundRect[i].tl().y == 1)	
		{
			rectangle(ROI_src_point, boundRect[i].tl(), boundRect[i].br(), Scalar(0,0,255), 2, 8, 0 );
			cout << boundRect[i].br().x - boundRect[i].tl().x << "********" << endl;
			double aa = boundRect[i].br().x - (boundRect[i].br().x - boundRect[i].tl().x) / 2.0;
			double bb = boundRect[i].br().y;
			Point2f p = Point2f(aa,bb);
			pin_point.push_back(p);

		}
	}
	cout << "^^^^^^^^^^^^^^^^^^"<< endl << pin_point << endl;
	//对尖点进行排序（轮廓选举出的为逆排序，我不知道其他情况轮廓的产生顺序， 最好进行一下排序）
	vector<Point> xx;
	vector<Point>::reverse_iterator it;
	for(it = pin_point.rbegin(); it != pin_point.rend(); it++)
	{
		xx.push_back(*it);
	}
	//冒泡排序
	for (unsigned int i = 0; i < xx.size() - 1; i++)
	{
		for(unsigned int j = i + 1; j < xx.size(); j++)
		{
			if(xx[i].x > xx[j].x)
			{
				Point p;
				p = xx[i];
				xx[i] = xx[j];
				xx[j] = p;
				cout << endl<< p << endl;
			}

		}
	}
	
	for(unsigned int i = 0; i < xx.size(); i ++)             //最终xx为需要的点集
	{
		xx[i].x += 650;
		xx[i].y += 1650;
	}
	for(unsigned int i = 0; i < xx.size(); i++)                            
	{
		circle(src, xx[i], 30,Scalar(0,0,255),0);
		circle(src, xx[i],2,Scalar(0,255,0),-1);
	}

//************************************【找出线的点集】********************************************************
	vector<vector<Point>> contours_line;
	vector<Vec4i> hierarchy_line;
	findContours(ROI_src_line_gray, contours_line, hierarchy_line, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
	//用最小矩形包围轮廓
	vector<Rect> boundRect_line( contours_line.size() );
	
	for( unsigned int i = 0; i < contours_line.size(); i++ )
	{
		boundRect_line[i] = boundingRect( Mat(contours_line[i]) );
	}

	vector<Point> line_point;
	//筛选出符合要求的矩形， 并计算出尖点
	for(unsigned  int i = 0; i< boundRect_line.size(); i++ )
	{	
		if(boundRect_line[i].br().y == 49 && boundRect_line[i].br().x - boundRect_line[i].tl().x > 15)						//筛选条件(49为1450-1400 从0开始的)	
		{
			rectangle( ROI_src_line, boundRect_line[i].tl(), boundRect_line[i].br(), Scalar(0,0,255), 2, 8, 0 );
			cout << boundRect_line[i].tl() << " " << boundRect_line[i].br() << endl;
			float aa = boundRect_line[i].br().x;
			float bb = boundRect_line[i].tl().y;
			Point2f p = Point2f(aa,bb);
			line_point.push_back(boundRect_line[i].tl());
			line_point.push_back(p);

			cout << p << endl;
		}
	}

	for(unsigned int i = 0; i < line_point.size(); i ++)             //最终line_point为需要的点集
	{
		line_point[i].x += 650;
		line_point[i].y += 1400;
	}
	for(unsigned int i = 0; i < line_point.size(); i++)                            
	{
		circle(src, line_point[i], 10,Scalar(0,0,255),0);
		circle(src, line_point[i],2,Scalar(0,255,0),-1);
	}

	//拟合直线
	Vec4f line_para;   
	cv::fitLine(line_point, line_para, CV_DIST_L2, 0, 0.01, 0.01);
	cout << endl<<line_para;

	//获取点斜式的点和斜率
	cv::Point2f point0;
	point0.x = line_para[2];
	point0.y = line_para[3];

	double k = line_para[1] / line_para[0];

	//计算直线的端点(y = k(x - x0) + y0)
	cv::Point2f point1, point2;
	point1.x = 0;
	point1.y = k * (0 - point0.x) + point0.y;
	point2.x = src.cols-100;
	point2.y = k * (src.cols-100 - point0.x) + point0.y;

	cv::line(src, point1,point2, cv::Scalar(255,0,0), 1, 8, 0);          //画出这条线

	//********************************************【求出端点到直线的距离】**************************************
	vector<double> solution;
	double A = point1.y - point2.y;
	double B = point2.x - point1.x;
	double C = point1.x * point2.y - point2.x * point1.y;

		cout <<"***********************"<<endl;
	for(unsigned int i = 0; i < xx.size(); i++)
	{
		double b = fabs(A * xx[i].x + B * xx[i].y + C);
		double n = b / sqrt(A * A + B * B);
		solution.push_back(n);
		cout << n << endl;
		string s = to_string(n);
		putText(src, s,xx[i],FONT_HERSHEY_SIMPLEX,0.5,Scalar(150,150,0),2,8);   //把数值写在旁边
	}

	




	namedWindow("nn", WINDOW_NORMAL);
	imshow("nn",src);
	namedWindow("canny", WINDOW_NORMAL);
	imshow("canny", ROI_src_point);
	namedWindow("hh", WINDOW_NORMAL);
	imshow("hh", ROI_src_line);
	cout << "canny检测";
	waitKey(0);
}

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