基于形态学运算的腐蚀，膨胀，开运算，闭运算

#include<iostream>

#include<opencv2/core/core.hpp>

#include<opencv2/highgui/highgui.hpp>

#include<opencv2/imgproc/imgproc.hpp>

using namespace std;

using namespace cv;

int main(){

Mat image = imread("binary.bmp");

imshow("Image",image);

////腐蚀图像 默认3*3

//Mat eroded;

//erode(image,eroded,Mat());

//imshow("Erode Image",eroded);

////膨胀图像

//Mat dilated;

//dilate(image, dilated, Mat());

//imshow("Dilate Image",dilated);

////以7*7大小的数据结构进行腐蚀

//Mat eroded2;

//Mat element(7, 7, CV_8U, Scalar(1));

//erode(image, eroded2, element);

//imshow("element Image",eroded2);

//// 以7*7大小的数据结构进行腐蚀3次

//Mat eroded3;

//Mat element3(7, 7, CV_8U, Scalar(1));

//erode(image,eroded3,element3,Point(-1,-1),3);

//imshow("eroded3",eroded3);

//对图片进行闭运算

Mat element5(5, 5, CV_8U, Scalar(1));

Mat closed;

morphologyEx(image, closed, MORPH_CLOSE, element5);

imshow("closed", closed);

//对图片进行开运算

Mat opened;

morphologyEx(image,opened,MORPH_OPEN,element5);

imshow("opened",opened);

//相继进行开运算和闭运算

Mat opencvandclose;

morphologyEx(image, opened, MORPH_OPEN, element5);

morphologyEx(opened, opencvandclose, MORPH_CLOSE, element5);

imshow("opencvandclose", opencvandclose);

//相继进行闭运算和开运算

Mat closeandopen;

morphologyEx(image, closed, MORPH_CLOSE, element5);

morphologyEx(closed, closeandopen, MORPH_OPEN, element5);

imshow("closeandopen", closeandopen);

//腐蚀图像 默认3*3

Mat eroded;

erode(image, eroded, element5);

imshow("Erode Image",eroded);

//先腐蚀在膨胀

Mat erodedanddilated;

Mat erodedanddilated2;

erode(image, erodedanddilated, element5);

dilate(erodedanddilated, erodedanddilated2, element5);

imshow("erodedanddilated", erodedanddilated2);

//先膨胀再腐蚀

Mat dilateanderode;

Mat dilateanderode2;

dilate(image, dilateanderode, element5);

erode(dilateanderode, dilateanderode2,element5);

imshow("dilateanderode", dilateanderode2);

//膨胀图像

Mat dilated;

dilate(image, dilated, element5);

imshow("Dilate Image",dilated);

waitKey(0);

}

erode(InputArray src, OutputArray dst, InputArray kernel, Point anchor=Point(-1,-1),int iterations=1, int borderType=BORDER_CONSTANT,

const Scalar& borderValue=morphologyDefaultBorderValue() )

iterations：腐蚀次数

我们的形态学滤波都作用在二值图像或者灰度图像上

闭运算：对图像进行先膨胀，再腐蚀

开运算：对图像先腐蚀，再膨胀

例子2：

加了滚动条，参考： http://blog.csdn.net/poem_qianmo/article/details/23710721 浅墨的博客

#include<iostream>
#include<opencv2/core/core.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/imgproc/imgproc.hpp>

using namespace std;
using namespace cv;

Mat src, dst;
int TrackbarNum = 0;
int StructElementSize = 3;

void process();
void on_TrackbarNumChange(int, void *);
void on_ElementSizeChange(int,void *);

int main(){
src = imread("1.jpg");
if (!src.data)
cout << "oh  no   not find" << endl;
imshow("image",src);

namedWindow("效果图");
Mat element = getStructuringElement(MORPH_RECT, Size(2 * StructElementSize + 1, 2 * StructElementSize + 1), Point(StructElementSize, StructElementSize));

erode(src,dst,element);
imshow("效果图",dst);

createTrackbar("腐蚀/膨胀", "效果图",&TrackbarNum, 1, on_TrackbarNumChange);
createTrackbar("内核值", "效果图", &StructElementSize, 21, on_ElementSizeChange);

cout << "begin"<<endl
<< "按下‘q’时，退出……" << endl;

while (char(waitKey(1)) != 'q'){}
return 0;

}

void process(){

Mat element = getStructuringElement(MORPH_RECT, Size(2 * StructElementSize + 1, 2 * StructElementSize + 1), Point(StructElementSize, StructElementSize));

if (TrackbarNum == 0){
erode(src,dst,element);
}
else
{
dilate(src,dst,element);
}

imshow("效果图",dst);

}

void on_TrackbarNumChange(int, void *){

process();

}
void on_ElementSizeChange(int, void *){

process();

}