OPENCV二值化图像内孔洞填充/小区域去除

来源：http://lib.csdn.net/article/opencv/28353

        原作者：robberjohn  博客已删除了，源码下载链接在

         http://download.csdn.net/download/robberjohn/8474913 

        http://blog.csdn.net/robberjohn/article/details/44081571

对于二值化图像，去除孔洞时采用的方法实际上与去除小区域相同，因此完全可以用同一个函数进行。

这两个功能可以采取区域生长法来实现。须注意，去除小区域时为保存有用信息，可采用8邻域探测，去除孔洞时则4邻域即可，否则容易泄露，出现靠边缘的孔洞未去除的情况。

效果（区域面积阈值为700）： 

原图像：

小面积区域去除：

孔洞填充结果：

源码

#include <cv.h>  #include <highgui.h>  #include <opencv2/imgproc/imgproc.hpp>    #include <opencv2/highgui/highgui.hpp>    #include <iostream>    #include <vector>        using namespace cv;  using namespace std;    void RemoveSmallRegion(Mat& Src, Mat& Dst, int AreaLimit=50, int CheckMode=1, int NeihborMode=0);    int main()    {        double t = (double)getTickCount();        char* imagePath = "E:\\SVM\\局部.jpg";      char* OutPath = "E:\\SVM\\局部_去除孔洞.jpg";            Mat Src = imread(imagePath, CV_LOAD_IMAGE_GRAYSCALE);      Mat Dst = Mat::zeros(Src.size(), CV_8UC1);              //二值化处理      for(int i = 0; i < Src.rows; ++i)        {            uchar* iData = Src.ptr<uchar>(i);          for(int j = 0; j < Src.cols; ++j)            {                if(iData[j] == 0 || iData[j]==255) continue;              else if (iData[j] < 10)                {                    iData[j] = 0;                    //cout<<'#';              }                else if (iData[j] > 10)                {                    iData[j] = 255;                   //cout<<'!';              }            }        }        cout<<"Image Binary processed."<<endl;        RemoveSmallRegion(Src, Dst, 20, 1, 1);      RemoveSmallRegion(Dst, Dst, 20, 0, 0);      cout<<"Done!"<<endl;      imwrite(OutPath, Dst);                t = ((double)getTickCount() - t)/getTickFrequency();      cout<<"Time cost: "<<t<<" sec."<<endl;        return 0;    }      //CheckMode: 0代表去除黑区域，1代表去除白区域; NeihborMode：0代表4邻域，1代表8邻域;  void RemoveSmallRegion(Mat& Src, Mat& Dst, int AreaLimit, int CheckMode, int NeihborMode)  {         int RemoveCount=0;       //记录除去的个数      //记录每个像素点检验状态的标签，0代表未检查，1代表正在检查,2代表检查不合格（需要反转颜色），3代表检查合格或不需检查      Mat Pointlabel = Mat::zeros( Src.size(), CV_8UC1 );            if(CheckMode==1)      {          cout<<"Mode: 去除小区域. ";          for(int i = 0; i < Src.rows; ++i)            {                uchar* iData = Src.ptr<uchar>(i);              uchar* iLabel = Pointlabel.ptr<uchar>(i);              for(int j = 0; j < Src.cols; ++j)                {                    if (iData[j] < 10)                    {                        iLabel[j] = 3;                   }                }            }        }      else      {          cout<<"Mode: 去除孔洞. ";          for(int i = 0; i < Src.rows; ++i)            {                uchar* iData = Src.ptr<uchar>(i);              uchar* iLabel = Pointlabel.ptr<uchar>(i);              for(int j = 0; j < Src.cols; ++j)                {                    if (iData[j] > 10)                    {                        iLabel[j] = 3;                   }                }            }        }        vector<Point2i> NeihborPos;  //记录邻域点位置      NeihborPos.push_back(Point2i(-1, 0));      NeihborPos.push_back(Point2i(1, 0));      NeihborPos.push_back(Point2i(0, -1));      NeihborPos.push_back(Point2i(0, 1));      if (NeihborMode==1)      {          cout<<"Neighbor mode: 8邻域."<<endl;          NeihborPos.push_back(Point2i(-1, -1));          NeihborPos.push_back(Point2i(-1, 1));          NeihborPos.push_back(Point2i(1, -1));          NeihborPos.push_back(Point2i(1, 1));      }      else cout<<"Neighbor mode: 4邻域."<<endl;      int NeihborCount=4+4*NeihborMode;      int CurrX=0, CurrY=0;      //开始检测      for(int i = 0; i < Src.rows; ++i)        {            uchar* iLabel = Pointlabel.ptr<uchar>(i);          for(int j = 0; j < Src.cols; ++j)            {                if (iLabel[j] == 0)                {                    //********开始该点处的检查**********                  vector<Point2i> GrowBuffer;                                      //堆栈，用于存储生长点                  GrowBuffer.push_back( Point2i(j, i) );                  Pointlabel.at<uchar>(i, j)=1;                  int CheckResult=0;                                               //用于判断结果（是否超出大小），0为未超出，1为超出                    for ( int z=0; z<GrowBuffer.size(); z++ )                  {                        for (int q=0; q<NeihborCount; q++)                                      //检查四个邻域点                      {                          CurrX=GrowBuffer.at(z).x+NeihborPos.at(q).x;                          CurrY=GrowBuffer.at(z).y+NeihborPos.at(q).y;                          if (CurrX>=0&&CurrX<Src.cols&&CurrY>=0&&CurrY<Src.rows)  //防止越界                          {                              if ( Pointlabel.at<uchar>(CurrY, CurrX)==0 )                              {                                  GrowBuffer.push_back( Point2i(CurrX, CurrY) );  //邻域点加入buffer                                  Pointlabel.at<uchar>(CurrY, CurrX)=1;           //更新邻域点的检查标签，避免重复检查                              }                          }                      }                    }                  if (GrowBuffer.size()>AreaLimit) CheckResult=2;                 //判断结果（是否超出限定的大小），1为未超出，2为超出                  else {CheckResult=1;   RemoveCount++;}                  for (int z=0; z<GrowBuffer.size(); z++)                         //更新Label记录                  {                      CurrX=GrowBuffer.at(z).x;                       CurrY=GrowBuffer.at(z).y;                      Pointlabel.at<uchar>(CurrY, CurrX) += CheckResult;                  }                  //********结束该点处的检查**********                  }            }        }          CheckMode=255*(1-CheckMode);      //开始反转面积过小的区域      for(int i = 0; i < Src.rows; ++i)        {            uchar* iData = Src.ptr<uchar>(i);          uchar* iDstData = Dst.ptr<uchar>(i);          uchar* iLabel = Pointlabel.ptr<uchar>(i);          for(int j = 0; j < Src.cols; ++j)            {                if (iLabel[j] == 2)                {                    iDstData[j] = CheckMode;               }                else if(iLabel[j] == 3)              {                  iDstData[j] = iData[j];              }          }        }             cout<<RemoveCount<<" objects removed."<<endl;  }  

一、对于二值图，0代表黑色，255代表白色。去除小连通区域与孔洞，小连通区域用8邻域，孔洞用4邻域。

 

  函数名字为：void RemoveSmallRegion(Mat &Src, Mat &Dst,int AreaLimit, int CheckMode, int NeihborMode)

     CheckMode: 0代表去除黑区域，1代表去除白区域; NeihborMode：0代表4邻域，1代表8邻域;  

如果去除小连通区域CheckMode=1,NeihborMode=1去除孔洞CheckMode=0，NeihborMode=0

     记录每个像素点检验状态的标签，0代表未检查，1代表正在检查,2代表检查不合格（需要反转颜色），3代表检查合格或不需检查 。

1.先对整个图像扫描，如果是去除小连通区域，则将黑色的背景图作为合格，像素值标记为3，如果是去除孔洞，则将白色的色素点作为合格，像素值标记为3。

2.扫面整个图像，对图像进行处理。

void RemoveSmallRegion(Mat &Src, Mat &Dst,int AreaLimit, int CheckMode, int NeihborMode){int RemoveCount = 0;//新建一幅标签图像初始化为0像素点，为了记录每个像素点检验状态的标签，0代表未检查，1代表正在检查,2代表检查不合格（需要反转颜色），3代表检查合格或不需检查 //初始化的图像全部为0，未检查Mat PointLabel = Mat::zeros(Src.size(), CV_8UC1);if (CheckMode == 1)//去除小连通区域的白色点{cout << "去除小连通域.";for (int i = 0; i < Src.rows; i++){for (int j = 0; j < Src.cols; j++){if (Src.at<uchar>(i, j) < 10){PointLabel.at<uchar>(i, j) = 3;//将背景黑色点标记为合格，像素为3}}}}else//去除孔洞，黑色点像素{cout << "去除孔洞";for (int i = 0; i < Src.rows; i++){for (int j = 0; j < Src.cols; j++){if (Src.at<uchar>(i, j) > 10){PointLabel.at<uchar>(i, j) = 3;//如果原图是白色区域，标记为合格，像素为3}}}}vector<Point2i>NeihborPos;//将邻域压进容器NeihborPos.push_back(Point2i(-1, 0));NeihborPos.push_back(Point2i(1, 0));NeihborPos.push_back(Point2i(0, -1));NeihborPos.push_back(Point2i(0, 1));if (NeihborMode == 1){cout << "Neighbor mode: 8邻域." << endl;NeihborPos.push_back(Point2i(-1, -1));NeihborPos.push_back(Point2i(-1, 1));NeihborPos.push_back(Point2i(1, -1));NeihborPos.push_back(Point2i(1, 1));}else cout << "Neighbor mode: 4邻域." << endl;int NeihborCount = 4 + 4 * NeihborMode;int CurrX = 0, CurrY = 0;//开始检测for (int i = 0; i < Src.rows; i++){for (int j = 0; j < Src.cols; j++){if (PointLabel.at<uchar>(i, j) == 0)//标签图像像素点为0，表示还未检查的不合格点{   //开始检查vector<Point2i>GrowBuffer;//记录检查像素点的个数GrowBuffer.push_back(Point2i(j, i));PointLabel.at<uchar>(i, j) = 1;//标记为正在检查int CheckResult = 0;for (int z = 0; z < GrowBuffer.size(); z++){for (int q = 0; q < NeihborCount; q++){CurrX = GrowBuffer.at(z).x + NeihborPos.at(q).x;CurrY = GrowBuffer.at(z).y + NeihborPos.at(q).y;if (CurrX >= 0 && CurrX<Src.cols&&CurrY >= 0 && CurrY<Src.rows)  //防止越界  {if (PointLabel.at<uchar>(CurrY, CurrX) == 0){GrowBuffer.push_back(Point2i(CurrX, CurrY));  //邻域点加入buffer  PointLabel.at<uchar>(CurrY, CurrX) = 1;           //更新邻域点的检查标签，避免重复检查  }}}}if (GrowBuffer.size()>AreaLimit) //判断结果（是否超出限定的大小），1为未超出，2为超出  CheckResult = 2;else{CheckResult = 1;RemoveCount++;//记录有多少区域被去除}for (int z = 0; z < GrowBuffer.size(); z++){CurrX = GrowBuffer.at(z).x;CurrY = GrowBuffer.at(z).y;PointLabel.at<uchar>(CurrY,CurrX)+=CheckResult;//标记不合格的像素点，像素值为2}//********结束该点处的检查**********  }}}CheckMode = 255 * (1 - CheckMode);//开始反转面积过小的区域  for (int i = 0; i < Src.rows; ++i){for (int j = 0; j < Src.cols; ++j){if (PointLabel.at<uchar>(i,j)==2){Dst.at<uchar>(i, j) = CheckMode;}else if (PointLabel.at<uchar>(i, j) == 3){Dst.at<uchar>(i, j) = Src.at<uchar>(i, j);}}}cout << RemoveCount << " objects removed." << endl;}