Random Number Generator(RNG) - OpenCV 난수 발생기 사용

Random number generator. It encapsulates the state (currently, a 64-bit integer) and has methods to return scalar random values and to fill arrays with random values. Currently, it supports uniform and Gaussian (normal) distributions. The generator uses Multiply-With-Carry algorithm, introduced by G. Marsaglia (http://en.wikipedia.org/wiki/Multiply-with-carry). Gaussian-distribution random numbers are generated using the Ziggurat algorithm (http://en.wikipedia.org/wiki/Ziggurat_algorithm), introduced by G. Marsaglia and W. W. Tsang.

아래 코드는 OpenCV에서 지원하는 난수 발생기의 사용 방법 입니다.

#include <opencv2/opencv.hpp>
 
using namespace std;
using namespace cv;
 
int main(int argc, char** argv)
{
    RNG rng(getTickCount());    // Constructor sets the state to the specified value.
    Mat mat(300, 400, CV_8SC3);
    
    // Fills arrays with random numbers.
    rng.fill(mat, RNG::UNIFORM, Scalar::all(0), Scalar::all(255));
    
    // Returns uniformly distributed integer random number from [a,b) range
    cout << "RNG::uniform()" << endl;
    cout << "- rng.uniform(0, 255): " << rng.uniform(0, 255) << endl;
    cout << "- rng.uniform(0.0f, 255.0f): " << rng.uniform(0.0f, 255.0f) << endl;
    cout << "- rng.uniform(0.0, 255.0): " << rng.uniform(0.0, 255.0) << endl << endl;
 
    // Returns a random integer sampled uniformly from [0, N).
    cout << "RNG::operator()" << endl;
    for (int i = 0; i < 5; i++)
        cout << "- rng(10): " << rng(10) << endl;
 
    // The method updates the state using the MWC algorithm and returns
    // the next 32-bit random number.
    cout << endl << "RNG::next()" << endl;
    for (int i = 0; i < 5; i++)
        cout << "- rng.next(): " << rng.next() << endl;
 
    imshow("RNG", mat);
 
    waitKey(0);
 
    return 0;
}

Matrix filled by RNG::fill().

Random numbers generated by RNG.