OPENCV二值化图像内孔洞填充/小区域去除（含效果图）

#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\\1.png"; char* OutPath = "E:\\SVM\\11.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; }