OPENCV去除小连通区域,去除孔洞的实例讲解

  • 2022-07-22 20:25:20

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。

OPENCV去除小连通区域,去除孔洞的实例讲解

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;
}

调用函数:dst是原来的二值图。

mat erzhi1 = mat::zeros(srcimage.rows, srcimage.cols, cv_8uc1);
removesmallregion(dst, erzhi,100, 1, 1);
removesmallregion(erzhi, erzhi,100, 0, 0);
imshow("erzhi1", erzhi);

OPENCV去除小连通区域,去除孔洞的实例讲解

和之前的图像相比

OPENCV去除小连通区域,去除孔洞的实例讲解

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