opencv4 学习 07 膨胀、腐蚀和开闭运算

膨胀：定义一个核，然后遍历整个图片，对于每个像素，以该像素为中心，使用核包裹范围内最大的像素值代替该像素值。所以最终高亮度的地方会膨胀。

腐蚀：定义一个核，然后遍历整个图片，对于每个像素，以该像素为中心，使用核包裹范围内最小的像素值代替该像素值。所以最终高亮度的地方会缩小。

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

using namespace std;
using namespace cv;

Mat src, erosion_dst, dilation_dst;

int erosion_elem = 0;
int erosion_size = 0;
int dilation_elem = 0;
int dilation_size = 0;
int const max_elem = 2;
int const max_kernel_size = 21;

void erosion(int, void*);
void dilation(int, void*);

int main(int argc, char* argv[])
{
    src = imread("LinuxLogo.jpg", IMREAD_COLOR);

    namedWindow("Erosion Demo", WINDOW_AUTOSIZE);
    namedWindow("Dilation Demo", WINDOW_AUTOSIZE);
    moveWindow("Dilation Demo", src.cols, 0);

    createTrackbar("Element:\n 0: Rect \n 1: Cross \n 2: Ellipse", "Erosion Demo", &erosion_elem, max_elem, erosion);
    createTrackbar("kernel size:\n 2n+1", "Erosion Demo", &erosion_size, max_kernel_size, erosion);
    createTrackbar("Element:\n 0: Rect \n 1: Cross \n 2: Ellipse", "Dilation Demo", &dilation_elem, max_elem, dilation);
    createTrackbar("kernel size:\n 2n+1", "Dilation Demo", &dilation_size, max_kernel_size,dilation);

    erosion(0,0);
    dilation(0,0);

    waitKey(0);
    return 0;
}

void erosion(int, void*){
    int erosion_type = 0;
    if(erosion_elem == 0){ erosion_type = MORPH_RECT;}
    else if(erosion_elem == 1){ erosion_type = MORPH_CROSS;}
    else if(erosion_elem == 2){ erosion_type = MORPH_ELLIPSE;}

    Mat element = getStructuringElement(erosion_type, Size(2*erosion_size+1, 2*erosion_size+1), Point(erosion_size,erosion_size));
    erode(src, erosion_dst, element);
    imshow("Erosion Demo", erosion_dst);
}
void dilation(int, void *){
    int dilation_type = 0;
    if(dilation_elem == 0){dilation_type = MORPH_RECT;}
    else if(dilation_elem == 1){ dilation_type = MORPH_CROSS;}
    else if(dilation_elem == 2){ dilation_type = MORPH_ELLIPSE;}

    Mat element = getStructuringElement(dilation_type, Size(2*dilation_size+1, 2*dilation_size+1), Point(dilation_size, dilation_size));
    dilate(src, dilation_dst, element);
    imshow("Dilation Demo", dilation_dst);
}

 

开运算：先腐蚀后膨胀，可以有效去除高光噪点

dst=open(src,element)=dilate(erode(src,element))

 

闭运算：先膨胀后腐蚀，可以有效去除低光的孔洞

dst=close(src,element)=erode(dilate(src,element))

 

形态学梯度：膨胀后的图像和腐蚀后的图像之间的差

dst=morphgrad(src,element)=dilate(src,element)−erode(src,element)

 

top hat：原始图想和开运算后的图像之间的差

dst=tophat(src,element)=src−open(src,element)

 

black hat：闭运算后的图像和原始图像之间的差

dst=blackhat(src,element)=close(src,element)−src

 

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

using namespace std;
using namespace cv;

Mat src, dst;
int morph_elem = 0;
int morph_size = 0;
int morph_operator = 0;
int const max_operator = 4;
int const max_elem = 2;
int const max_kernel_size = 21;

const char* window_name = "Morphology Transformations Demo";

void morphology_operations(int, void*);

int main(int argc, char* argv[])
{
    namedWindow(window_name, WINDOW_AUTOSIZE);
    src = imread("baboon.jpg", IMREAD_COLOR);

    createTrackbar("Operator:\n 0: Opening - 1: Closing \n 2: Gradient - 3: Top Hat \n 4: Black Hat", window_name,
                   &morph_operator, max_operator, morphology_operations);
    createTrackbar("Element:\n 0: Rect - 1: Cross - 2: Ellipse", window_name, &morph_elem, max_elem, morphology_operations);
    createTrackbar("kernel size:\n 2n+1", window_name, &morph_size, max_kernel_size, morphology_operations);

    morphology_operations(0,0);

    waitKey(0);
    return 0;
}

void morphology_operations(int, void*){

    int operation = morph_operator + 2;

    Mat element = getStructuringElement(morph_elem, Size(2*morph_size+1,2*morph_size+1),Point(morph_size,morph_size));
    morphologyEx(src,dst,operation,element);
    imshow(window_name,dst);

}

 

参考：

https://docs.opencv.org/3.4/db/df6/tutorial_erosion_dilatation.html

https://docs.opencv.org/3.4/d3/dbe/tutorial_opening_closing_hats.html