Opencv检测出图片中条形码 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(); 
}