Question

Opencv问题， 怎样去除二值图像中面积较小的连通域？

Answer 1

//=======函数实现=====================================================================
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 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;
}
//=======函数实现=====================================================================

//=======调用函数=====================================================================
Mat img;
img = imread("D:\\1_1.jpg", 0);//读取图片
threshold(img, img, 128, 255, CV_THRESH_BINARY_INV);
imshow("去除前", img);
Mat img1;
RemoveSmallRegion(img, img, 200, 0, 1);
imshow("去除后", img);
waitKey(0);
//=======调用函数=====================================================================