图像形态学操作—腐蚀扩展深度

全栈程序员-站长 • 2022年1月14日下午12:00 • 未分类 • 阅读 49

大家好，又见面了，我是全栈君，今天给大家准备了Idea注册码。

在这里，我们想向大家解释这本书的数字图像处理对冈萨雷斯的扩大和使用腐蚀-definedopencv取得的成果，然后控制它们之间的差异。

一：opencv达到

在这之前能够看我的另外一篇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：

图像形态学操作—腐蚀扩展深度

膨胀就是假设结构元B有一处非0，而A相应位置非0，则求出A中与B中相应非0处所有像素最大值来取代当前像素点值。Opencv中默认的结构元是3*3的矩阵，所有非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：

图像形态学操作—腐蚀扩展深度