1、目的
把图片转换为灰度图，之后进行2次1倍图像尺寸缩写 ，再进行边沿检测。
2、代码
#include <opencv2/opencv.hpp>
void help(char** argv ) {
std::cout << "\n"
<< "\nExample 2-8. Combining the pyramid down operator (twice) and the Canny"
<< "\n subroutine in a simple image pipeline"
<< "\nCall:\n"
<< argv[0] <<" <path/image>\n"
<< "For example:\n"
<< argv[0] << " ../fruits.jpg\n"
<< std::endl;
}
int main( int argc, char** argv ) {
if (argc != 2) {
help(argv);
return 0;
}
cv::Mat img_rgb, img_gry, img_cny, img_pyr, img_pyr2;
cv::namedWindow( "Example Gray", cv::WINDOW_AUTOSIZE );
cv::namedWindow( "Example Canny", cv::WINDOW_AUTOSIZE );
img_rgb = cv::imread( argv[1] );
cv::cvtColor( img_rgb, img_gry, cv::COLOR_BGR2GRAY);//转换为灰度图
cv::pyrDown( img_gry, img_pyr ); //缩写一倍尺寸
cv::pyrDown( img_pyr, img_pyr2 );//缩写一倍尺寸
cv::Canny( img_pyr2, img_cny, 10, 100, 3, true ); //边沿检测
cv::imshow( "Example Gray", img_gry );
cv::imshow( "Example Canny", img_cny );
cv::waitKey(0);
}
3、结果
