OpenCV  3.4.19
Open Source Computer Vision
samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp

Sample code using Sobel and/or Scharr OpenCV functions to make a simple Edge Detector

Sobel_Derivatives_Tutorial_Result.jpg
Sample screenshot

Check the corresponding tutorial for more details

#include <iostream>
using namespace cv;
using namespace std;
int main( int argc, char** argv )
{
cv::CommandLineParser parser(argc, argv,
"{@input |lena.jpg|input image}"
"{ksize k|1|ksize (hit 'K' to increase its value at run time)}"
"{scale s|1|scale (hit 'S' to increase its value at run time)}"
"{delta d|0|delta (hit 'D' to increase its value at run time)}"
"{help h|false|show help message}");
cout << "The sample uses Sobel or Scharr OpenCV functions for edge detection\n\n";
parser.printMessage();
cout << "\nPress 'ESC' to exit program.\nPress 'R' to reset values ( ksize will be -1 equal to Scharr function )";
// First we declare the variables we are going to use
Mat image,src, src_gray;
Mat grad;
const String window_name = "Sobel Demo - Simple Edge Detector";
int ksize = parser.get<int>("ksize");
int scale = parser.get<int>("scale");
int delta = parser.get<int>("delta");
int ddepth = CV_16S;
String imageName = parser.get<String>("@input");
// As usual we load our source image (src)
image = imread( samples::findFile( imageName ), IMREAD_COLOR ); // Load an image
// Check if image is loaded fine
if( image.empty() )
{
printf("Error opening image: %s\n", imageName.c_str());
return EXIT_FAILURE;
}
for (;;)
{
// Remove noise by blurring with a Gaussian filter ( kernel size = 3 )
GaussianBlur(image, src, Size(3, 3), 0, 0, BORDER_DEFAULT);
// Convert the image to grayscale
cvtColor(src, src_gray, COLOR_BGR2GRAY);
Mat grad_x, grad_y;
Mat abs_grad_x, abs_grad_y;
Sobel(src_gray, grad_x, ddepth, 1, 0, ksize, scale, delta, BORDER_DEFAULT);
Sobel(src_gray, grad_y, ddepth, 0, 1, ksize, scale, delta, BORDER_DEFAULT);
// converting back to CV_8U
convertScaleAbs(grad_x, abs_grad_x);
convertScaleAbs(grad_y, abs_grad_y);
addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 0, grad);
imshow(window_name, grad);
char key = (char)waitKey(0);
if(key == 27)
{
return EXIT_SUCCESS;
}
if (key == 'k' || key == 'K')
{
ksize = ksize < 30 ? ksize+2 : -1;
}
if (key == 's' || key == 'S')
{
scale++;
}
if (key == 'd' || key == 'D')
{
delta++;
}
if (key == 'r' || key == 'R')
{
scale = 1;
ksize = -1;
delta = 0;
}
}
return EXIT_SUCCESS;
}