OpenCV 检测二维码并定位

今天药忘吃喽~ 2022-07-12 02:44 457阅读 0赞

**注意：该程序功能是检测二维码，不是识别，只是在图中定出二维码的位置即可**

原图是这样：如果出现这张图片时，程序需要找到二维码

![这里写图片描述][da0bef937a90cf1ca02872d863aeb6c5.png]

其余图片是这样：

![这里写图片描述][6c59eab32bf9c29b7b745db6a601ecb7.png]

程序步骤：  
1.图片缩小  
2.灰度化，直方图均衡化，对比度增强，滤波  
3.otsu阈值分割  
4.五次膨胀  
5.轮廓查找，如果轮廓满足一下条件，认为可能为二维码区域，像素面积大于60，长短轴之比小于1.3  
6.对疑似区域做判断，因为本实验二维码贴在大概中心位置，找到疑似轮廓的质心，判断质心是不是在图片长宽的三分之一到三分之二之间，如果是认为是二维码区域  
7.对二维码区域画成蓝色

#include <stdio.h>  
    #include <opencv/highgui.h>  
    #include <time.h>  
    #include <opencv2/opencv.hpp>  
    #include <opencv/cv.h>  
    #include <iostream> 
    
    using namespace std;  
    using namespace cv; 
    
    int main(int argc,char *argv[])  
    {
    	
    	Mat srcImage;
    	Mat resizeImage;
    	Mat grayImage;
    	Mat equalizeHistImage;
    	Mat contrastandbrightImage;
    	Mat sobelImage;
    	Mat thresholdImage;
    	Mat dilateImage;
    	Mat areaImage;
    	Mat ellipseImage;
    	srcImage = imread("3.jpg");
    	Size dsize = Size(srcImage.cols*0.3,srcImage.rows*0.3);
    	resize(srcImage, resizeImage,dsize);
    	cvtColor(resizeImage,grayImage,CV_BGR2GRAY);
    	equalizeHist(grayImage,equalizeHistImage);
    	亮度、对比度增强
    	contrastandbrightImage= Mat::zeros( equalizeHistImage.size(), equalizeHistImage.type() ); 
    	for(int y = 0; y < equalizeHistImage.rows; y++ )  
    	{  
    		for(int x = 0; x <equalizeHistImage.cols; x++ )  
    		{  
    			contrastandbrightImage.at<uchar>(y,x)= saturate_cast<uchar>(6*(equalizeHistImage.at<uchar>(y,x) ));  	
    		} 
    	} 
    	blur(contrastandbrightImage,contrastandbrightImage,Size(3,3));  
    	//Sobel(contrastandbrightImage, sobelImage, CV_8U, 0,1 ,1, 1, 0, BORDER_DEFAULT);
    	threshold(contrastandbrightImage,thresholdImage, 0, 255, CV_THRESH_OTSU+CV_THRESH_BINARY_INV);  
    	Mat element = getStructuringElement(MORPH_RECT, Size(3, 3));  
    	//进行膨胀操作  
    	dilate(thresholdImage, dilateImage, element);  
    	dilate(dilateImage, dilateImage, element);
    	dilate(dilateImage, dilateImage, element);  
    	dilate(dilateImage, dilateImage, element);  
    	dilate(dilateImage, dilateImage, element);  
    
    	//dilateImage.copyTo(areaImage);
    	//vector< vector< Point> > contours;  
    	//findContours(areaImage,contours,CV_RETR_TREE,  CV_CHAIN_APPROX_NONE); 
    	//vector<vector<Point> >::iterator itc= contours.begin();  
    	//while (itc!=contours.end()) 
    	//{  
    	//	if( itc->size()<100)
    	//	{  
    	//		itc= contours.erase(itc);  
    	//	}
    	//   else
    	//   {
    	//	   ++itc;  
    	//	}
    	//}  
    	//drawContours(areaImage, contours, -1, Scalar(255), CV_FILLED);
    
    	//找轮廓 两步判断  一个是大小  一个是长短轴比比  认为面积比60大，长短轴比比1.3小的区域是二维码区域  再做下一步判断
    	dilateImage.copyTo(ellipseImage);
    	vector<vector<Point> > twocontours;
    	vector<Vec4i>twohierarchy;
    	findContours(ellipseImage,twocontours,twohierarchy,CV_RETR_TREE,CV_CHAIN_APPROX_SIMPLE);  
    	vector<Moments> mu(twocontours.size() );      
        vector<Point2f> mc( twocontours.size() );
    	for(int k = 0; k < (int)twocontours.size(); k++)    //查找轮廓
    	{
    		if (int(twocontours.at(k).size()) <=60)//轮廓面积小于60的不处理
    		{
    			drawContours(ellipseImage, twocontours, k, Scalar(0), CV_FILLED);
    		}
    		else
    		{
    			RotatedRect rRect = fitEllipse(twocontours.at(k)); 
    			double majorAxis = rRect.size.height > rRect.size.width ? rRect.size.height : rRect.size.width;
    			double minorAxis = rRect.size.height > rRect.size.width ? rRect.size.width : rRect.size.height;
    			float rate = majorAxis/minorAxis;
    			if (rate<1.3)   //长短轴之比小于1.4的轮廓
    			{
    				//可能为二维码的区域，判断是否为二维码区域
    				printf("%f\n",rate);
    				//求区域的质心
    				mu[k] = moments( twocontours[k], false );   
    				mc[k] = Point2d( mu[k].m10/mu[k].m00 , mu[k].m01/mu[k].m00 ); 
    				//打印质心
    				printf("x=%f,y=%f\n",mc[k].x,mc[k].y);
    				//打印图像的长宽
    				printf("图像的长%d，图像的宽%d\n",resizeImage.cols,resizeImage.rows);
    				//画出质心
    				Point center = Point(mc[k].x,mc[k].y);  
    				int r = 10;    
    				circle(resizeImage,center,r,Scalar(255,0,0));  
    				//判断质心是不是在图像中间   三分之一 < 质心 < 三分之二
    				if ((int)mc[k].x<(int)2*(resizeImage.cols/3)&&(int)mc[k].x>(int)(resizeImage.cols/3))
    				{
    					if ((int)mc[k].y<(int)2*(resizeImage.rows/3)&&(int)mc[k].y>(int)(resizeImage.rows/3))
    					{
    							drawContours(resizeImage, twocontours, k, Scalar(255,0,0), CV_FILLED);//把轮廓涂成蓝色
    							printf("蓝色是二维码区域\n");
    					}
    				}
    			}
    			else  //长短轴之比大于1.4的轮廓  不是二维码区域
    			{
    				drawContours(resizeImage, twocontours, k, Scalar(0,0,255), CV_FILLED);//把轮廓涂成红色
    			}
    		}
    	}		
    	imshow("缩小图",resizeImage);
    	imshow("灰度图",grayImage);
    	imshow("对比度和亮度增强",contrastandbrightImage);
    	//imshow("soble检测",sobelImage);
    	imshow("二值化结果",thresholdImage);
    	imshow("膨胀",dilateImage);
    	//imshow("删除小面积",areaImage);
    	imshow("长短轴",ellipseImage);
    	waitKey(0);
    }

部分结果图：

![这里写图片描述][18aefef440914d93ade8aabb843f0717.png]

![这里写图片描述][a1f770b4be1a2c880953dc22bd66bdca.png]

无二维码图片的结果图：

![这里写图片描述][265e671046360df35890b6762d126c91.png]

[da0bef937a90cf1ca02872d863aeb6c5.png]: /images/20220711/dbc6ea4f65a24b7fb51a13b33d03cd5a.png
[6c59eab32bf9c29b7b745db6a601ecb7.png]: /images/20220711/3a0ef93774a048e58b00465336244ef1.png
[18aefef440914d93ade8aabb843f0717.png]: /images/20220711/e9d0192c48ad4a7b968ca8573855e8e6.png
[a1f770b4be1a2c880953dc22bd66bdca.png]: /images/20220711/3fb2ab91058640ea8165b4262434f12b.png
[265e671046360df35890b6762d126c91.png]: /images/20220711/ebcf6bc63ba240cd8b587fc2b007c408.png