C++ Opencv自寫函數實現膨脹腐蝕處理技巧

#include <opencv2/opencv.hpp>
#include <iostream>

using namespace std;
using namespace cv;

//定義腐蝕函數
void myErode(Mat Src, Mat Tem, Mat Dst)
{
	int m = (Tem.rows - 1) / 2;
	int n = (Tem.cols - 1) / 2;
	for (int i = m; i < Src.rows - m; i++)//i、j的范圍保證結構元始終在擴展後的圖像內部
	{
		for (int j = n; j < Src.cols - n; j++)
		{
			Mat SrcROI = Src(Rect(j - m, i - n, Tem.cols, Tem.rows));
			double sum = 0;
			sum = SrcROI.dot(Tem);//矩陣對應位置相乘後求和
			if (sum == 9)//結構元的9個元素均為1，和為9才能保證結構元完全包含於相應集合
				Dst.at<uchar>(i, j) = 255;
			else
				Dst.at<uchar>(i, j) = 0;
		}
	}
}

//定義膨脹函數
void myDilate(Mat Src, Mat Tem, Mat Dst)
{
	int m = (Tem.rows - 1) / 2;
	int n = (Tem.cols - 1) / 2;
	for (int i = m; i < Src.rows - m; i++)//i、j的范圍保證結構元始終在擴展後的圖像內部
	{
		for (int j = n; j < Src.cols - n; j++)
		{
			Mat SrcROI = Src(Rect(j - m, i - n, Tem.cols, Tem.rows));
			double sum = 0;
			sum = SrcROI.dot(Tem);//矩陣對應位置相乘後求和
			if (sum != 0)//結構元的9個元素均為1，隻要和不為0，就能說明結構元與相應集合有交集
				Dst.at<uchar>(i, j) = 255;
			else
				Dst.at<uchar>(i, j) = 0;
		}
	}
}

int main()
{
	Mat mImage = imread("dada.jpg", 0);
	if (mImage.data == 0)
	{
		cerr << "Image reading error !" << endl;
		system("pause");
		return -1;
	}
	namedWindow("The original image", WINDOW_NORMAL);
	imshow("The original image", mImage);

	//設置閾值將圖像二值化
	const int binThreshold = 80;
	for (int i = 0; i < mImage.rows; i++)
	{
		uchar* pImage = mImage.ptr<uchar>(i);
		for (int j = 0; j < mImage.cols; j++)
		{
			if (pImage[j] > binThreshold)//事實上應將灰度值大於閾值的賦值為255，但為瞭方便後續膨脹腐蝕的計算，在這裡將其賦值為1
				pImage[j]= 1;
			else
				pImage[j] = 0;
		}
	}

	//定義並初始化結構元
	Mat mTemplate(3, 3, CV_8UC1, Scalar(1));
	if (mTemplate.rows * mTemplate.cols % 2 == 0)
	{
		cerr << "The size doesn't meet the requirement !" << endl;
		system("pause");
		return -1;
	}
	
	//擴展圖像邊界
	copyMakeBorder(mImage, mImage, mTemplate.rows, mTemplate.rows, mTemplate.cols, mTemplate.cols, BORDER_CONSTANT, Scalar(0));

	//進行圖像腐蝕
	Mat mEResult = mImage.clone();
	myErode(mImage, mTemplate, mEResult);

	//進行圖像膨脹
	Mat mDResult = mImage.clone();
	myDilate(mImage, mTemplate, mDResult);

	//進行顯示
	namedWindow("The eroding image", WINDOW_NORMAL);
	imshow("The eroding image", mEResult);
	namedWindow("The dilating image", WINDOW_NORMAL);
	imshow("The dilating image", mDResult);
	waitKey();
	destroyAllWindows();

	return 0;
}

#include <opencv2/opencv.hpp>
#include <iostream>

using namespace std;
using namespace cv;

int main()
{
	uchar A[3][3] = { {1,2,3},{4,5,6},{7,8,9} };
	uchar B[3][3] = { { 1,1,1 },{ 1,1,1 },{ 1,1,1 } };
	Mat Src(3, 3, CV_8UC1, A);
	Mat Dst(3, 3, CV_8UC1, B);
	double Result = Src.dot(Dst);
	cout << "Src：" << Src << endl;
	cout << "Dst：" << Dst << endl;
	cout << "Result：" << Result << endl;
	system("pause");
	return 0;
}

#include <opencv2/opencv.hpp>
#include <iostream>

using namespace std;
using namespace cv;

int main()
{
	uchar A[3][3] = { {1,2,3},{4,5,6},{7,8,9} };
	uchar B[3][3] = { { 1,1,1 },{ 1,1,1 },{ 1,1,1 } };
	Mat Src(3, 3, CV_8UC1, A);
	Mat Dst(3, 3, CV_8UC1, B);
	Mat Result = Src.mul(Dst);
	cout << "Src：" << Src << endl;
	cout << "Dst：" << Dst << endl;
	cout << "Result：" << Result << endl;
	system("pause");
	return 0;
}