图像形态学操作—腐蚀膨胀深入

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图像形态学操作—腐蚀膨胀深入

2024-07-10 11:37:07 227人阅读

这里我们主要想讲解冈萨雷斯的数字图像处理这本书上膨胀腐蚀的定义及用opencv实现的结果，然后对比它们之间的差异。

一：opencv实现

在这之前可以看我的另外一篇blog：http://blog.csdn.net/lu597203933/article/details/17184439

膨胀：

案例代码：

int main()
{
	int a[8][8] = {
		{0,0,0,0,0,0,0,0}, 
		{0,0,5,1,0,0,1,1}, 
		{0,1,0,1,0,1,0,0},
		{0,1,1,2,1,0,1,0},
		{0,0,0,1,0,1,0,0},
		{0,1,0,0,0,0,0,1},
		{0,0,0,0,0,0,0,0},
		{0,0,0,0,0,0,0,0}
	};
	Mat S = Mat::zeros(8, 8, CV_8UC1);
	for(int j = 0; j < S.rows; j++)
	{
		for(int i = 0; i < S.cols; i++)
		{
			S.at<uchar>(j,i) = a[j][i];
		}
	}
	cout << "S = " << endl << " " << S << endl;
	Mat result;
	Mat dilated = Mat::zeros(3, 3, CV_8UC1);
	dilated.at<uchar>(0,1) = 1;
	//eroded.at<uchar>(0,2) = 1;
	dilated.at<uchar>(1,0) = 1;
	dilated.at<uchar>(1,1) = 2;          // 结构元素非0即1
	dilated.at<uchar>(1,2) = 1;
	dilated.at<uchar>(2,1) = 1;
	cout << "dilated = " << endl << " " << dilated << endl;	
	dilate(S, result, dilated);  
	cout << "result = " << endl << " " << result << endl;
	return 0;
}

结果：

膨胀就是如果结构元B有一处非0，而A对应位置非0，则求出A中与B中对应非0处所有像素最大值来代替当前像素点值。Opencv中默认的结构元是3*3的矩阵，全部非0。

腐蚀：

案例代码：

int main()
{
	int a[8][8] = {
		{0,0,0,0,0,0,0,0}, 
		{0,0,5,1,0,0,1,1}, 
		{0,1,0,1,0,1,0,0},
		{0,1,1,2,1,0,1,0},
		{0,0,0,1,0,1,0,0},
		{0,1,0,0,0,0,0,1},
		{0,0,0,0,0,0,0,0},
		{0,0,0,0,0,0,0,0}
	};
	Mat S = Mat::zeros(8, 8, CV_8UC1);
	for(int j = 0; j < S.rows; j++)
	{
		for(int i = 0; i < S.cols; i++)
		{
			S.at<uchar>(j,i) = a[j][i];
		}
	}
	cout << "S = " << endl << " " << S << endl;
	Mat result;
	Mat eroded = Mat::zeros(3, 3, CV_8UC1);
	eroded.at<uchar>(0,1) = 1;
	//eroded.at<uchar>(0,2) = 1;
	eroded.at<uchar>(1,0) = 1;
	eroded.at<uchar>(1,1) = 2;          // 结构元素非0即1
	eroded.at<uchar>(1,2) = 1;
	eroded.at<uchar>(2,1) = 1;
	cout << "eroded = " << endl << " " << eroded << endl;	
	erode(S, result, eroded);  
	cout << "result = " << endl << " " << result << endl;
	return 0;

结果：