OpenCV learning: basic image manipulation (6): morphological manipulation

Basic concept

corrosion

Corrosion can be understood as the center of B (anchor point) walking along the inner boundary of A in a circle. For corrosion also highlight part , portions other than the region A <highlight pixel A , which is substituted in the outside.

Swell

Expansion can be understood as the center of B (anchor point) walking along the outer boundary of A in a circle. For expansion is highlight part , portions other than the region A <highlight pixel A , which is substituted in the outside.

Open operation

By for the first 腐蚀operation, then 膨胀the operation obtained. We are very useful when removing small objects (assuming that the object is bright and the foreground color is black), which is used to erase noise that is brighter than the background .

Closed operation

闭运算It is a reverse operation of the opening operation, in particular to be 膨胀then 腐蚀operated , used to erase darker than the background noise .

Morphological gradient

Subtracting the corroded image from the dilated image can be used to extract the edges in the picture.

Top hat algorithm

The difference between the original image and the image after the opening operation is used to extract the bright small target foreground.

Black hat algorithm

The difference between the original image and the image after the operation, and the non-highlight small target foreground is taken out.

API introduction

Expansion and corrosion

//获取，卷积核
Mat structureElement = getStructuringElement(MORPH_RECT, Size(s, s), Point(-1, -1));
//指定                                       卷积核形状     大小      锚点位置（-1为中心）      


dilate(src, dst, structureElement, Point(-1, -1), 1);
//    源图  结果   卷积核             锚点      迭代次数

erode(src, dst, structureElement);
//默认 锚点为中心点  迭代次数为 1

Other morphological operations

//同样先获得，卷积核：
// MORPH_RECT  矩形    MORPH_CROSS  十字形    MORPH_ELLIPSE   椭圆形
Mat structureElement = getStructuringElement(MORPH_RECT, Size(s, s), Point(-1, -1));

//调用morphologyEx
morphologyEx(src, dst, MORPH_BLACKHAT, structureElement);
//          原图，结果，运算类型         运算核 


/*******************************************************************************

MORPH_CLOSE  闭
MORPH_OPEN   开
MORPH_GRADIENT   梯度
MORPH_TOPHAT      顶帽
MORPH_BLACKHAT    黑帽
MORPH_DILATE      膨胀
MORPH_ERODE       腐蚀
*********************************************************************************/      

Code practice

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

using namespace cv;
using namespace std;
Mat src,dst;
int element_size = 3;
int max_size = 25;
char OUTPUT[] = "OUTPUT_WINDOS";

void CallBack_Demo(int, void*)
{
	int s = element_size * 2 + 1;
	Mat structureElement = getStructuringElement(MORPH_RECT, Size(s, s), Point(-1, -1));
	//膨胀与腐蚀
	//dilate(src, dst, structureElement, Point(-1, -1), 1);
	//erode(src, dst, structureElement);

	//闭
	//morphologyEx(src,dst,MORPH_CLOSE,structureElement);
        //开
	//morphologyEx(src, dst, MORPH_OPEN, structureElement);
	//梯度
	//morphologyEx(src, dst, MORPH_GRADIENT, structureElement);
	//顶帽
	//morphologyEx(src, dst,MORPH_TOPHAT , structureElement);
	//黑帽
	morphologyEx(src, dst, MORPH_BLACKHAT, structureElement);
	imshow(OUTPUT, dst);
	return;
}


int main(int argc, char* argv[])
{
	//src = imread("src.jpg");
	src = imread("1.PNG");
	if (!src.data)
	{
		cout << "cannot open image" << endl;
		return -1;
	}
	namedWindow("input image", WINDOW_AUTOSIZE);
	imshow("input image",src);
	namedWindow(OUTPUT,WINDOW_AUTOSIZE);
	createTrackbar("Element Size:", OUTPUT, &element_size, max_size, CallBack_Demo);
	CallBack_Demo(0, 0);
	waitKey(0);
	return 0;
}