10个步骤Opencv轻松检测出图片中条形码

#include "core/core.hpp" #include "highgui/highgui.hpp" #include "imgproc/imgproc.hpp"  using namespace cv;  int main(int argc,char *argv[]) {   Mat image,imageGray,imageGuussian;   Mat imageSobelX,imageSobelY,imageSobelOut;   image=imread(argv[1]);    //1. 原图像大小调整，提高运算效率   resize(image,image,Size(500,300));   imshow("1.原图像",image);    //2. 转化为灰度图   cvtColor(image,imageGray,CV_RGB2GRAY);   imshow("2.灰度图",imageGray);    //3. 高斯平滑滤波   GaussianBlur(imageGray,imageGuussian,Size(3,3),0);   imshow("3.高斯平衡滤波",imageGuussian);    //4.求得水平和垂直方向灰度图像的梯度差,使用Sobel算子   Mat imageX16S,imageY16S;   Sobel(imageGuussian,imageX16S,CV_16S,1,0,3,1,0,4);   Sobel(imageGuussian,imageY16S,CV_16S,0,1,3,1,0,4);   convertScaleAbs(imageX16S,imageSobelX,1,0);   convertScaleAbs(imageY16S,imageSobelY,1,0);   imageSobelOut=imageSobelX-imageSobelY;   imshow("4.X方向梯度",imageSobelX);   imshow("4.Y方向梯度",imageSobelY);   imshow("4.XY方向梯度差",imageSobelOut);     //5.均值滤波，消除高频噪声   blur(imageSobelOut,imageSobelOut,Size(3,3));   imshow("5.均值滤波",imageSobelOut);     //6.二值化   Mat imageSobleOutThreshold;   threshold(imageSobelOut,imageSobleOutThreshold,180,255,CV_THRESH_BINARY);     imshow("6.二值化",imageSobleOutThreshold);    //7.闭运算，填充条形码间隙   Mat element=getStructuringElement(0,Size(7,7));   morphologyEx(imageSobleOutThreshold,imageSobleOutThreshold,MORPH_CLOSE,element);     imshow("7.闭运算",imageSobleOutThreshold);    //8. 腐蚀，去除孤立的点   erode(imageSobleOutThreshold,imageSobleOutThreshold,element);   imshow("8.腐蚀",imageSobleOutThreshold);    //9. 膨胀，填充条形码间空隙，根据核的大小，有可能需要2~3次膨胀操作   dilate(imageSobleOutThreshold,imageSobleOutThreshold,element);   dilate(imageSobleOutThreshold,imageSobleOutThreshold,element);   dilate(imageSobleOutThreshold,imageSobleOutThreshold,element);   imshow("9.膨胀",imageSobleOutThreshold);      vector<vector<Point>> contours;   vector<Vec4i> hiera;    //10.通过findContours找到条形码区域的矩形边界   findContours(imageSobleOutThreshold,contours,hiera,CV_RETR_EXTERNAL,CV_CHAIN_APPROX_NONE);   for(int i=0;i<contours.size();i++)   {     Rect rect=boundingRect((Mat)contours[i]);     rectangle(image,rect,Scalar(255),2);     }     imshow("10.找出二维码矩形区域",image);    waitKey(); }