发布时间：2025-06-24 19:07:48 作者：北方职教升学中心 阅读量：826
2代表检查不合格（需要反转颜色），3代表检查合格或不需要检查 ///所有初始化图像均为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;///标记背景黑点合格，像素为3 } } } } else//去除孔洞黑色点像素 { //cout << "除孔"; 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，标记合格，像素为3 } } } } vector<Point2i>NeihborPos;///将邻域压入容器 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 int a = 0;//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)//标签图像素点0，表示未检查的不合格点尚未检查 { //开始检查 vector<Point2i>GrowBuffer;///记录检查像素点的数量 GrowBuffer.push_back(Point2i(j, i)); PointLabel.at<uchar>(i, j) = 1;///标记正在检查中 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)); //在邻域点添加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（是否超过限定大小），11不超过，2为超出 CheckResult = 2; else { CheckResult = 1; RemoveCount++;//记录有多少区域被删除 } 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 } //。
方法一流程：
//=======函数实现=====================================================================void RemoveSmallRegion(Mat &Src, Mat &Dst, int AreaLimit, int CheckMode, int NeihborMode){ int RemoveCount = 0; //新标签图像初始化为0像素点，用于记录每个像素检测状态的标签，0代表未检查1代表正在检查，【C++介绍】。
opencv实现有更好的算法，您可以参考本博客OpenCV去除面积较小的连通域_c#opencv 筛选小区域-CSDN博客。
但是opencvsharp没有对应的同类算法为了照顾C#编程学生，因此将 将面积较小的连通域算法删除为C#代码。
