getGaussianKernel

getGaussianKernel : Returns Gaussian filter coefficients.
getGaussianKernel(int ksize, double sigma, int ktype=CV_64F )

ksize – Aperture size. It should be odd ( \texttt{ksize} \mod 2 = 1 ) and positive.

sigma – Gaussian standard deviation. If it is non-positive, it is computed from ksize as sigma = 0.3*((ksize-1)*0.5 - 1) + 0.8 .

ktype – Type of filter coefficients. It can be CV_32f or CV_64F .

int M = 101;

double sigma = 10;

Mat_ g = getGaussianKernel(M, sigma, CV_64F);

for(int i=0; i

{

double g1 = g(i,0);

Dbg("%f", g1);

}

Mat_ 접근

// more convenient forms of row and element access operators 

    _Tp* operator [](int y);

    const _Tp* operator [](int y) const;

    _Tp& operator ()(int row, int col);

    const _Tp& operator ()(int row, int col) const;

    _Tp& operator ()(Point pt);

    const _Tp& operator ()(Point pt) const;

아래는 http://bytefish.de/blog/opencv/code_snippets/ 에서 가져옴

template

void printMat(const cv::Mat_<_tp>& mat) {

    typedef typename DataType<_tp>::work_type _wTp;

    for(int i = 0; i < mat.rows; i++)

        for(int j=0; j < mat.cols; j++)

            cout << (_wTp) mat(i,j) << " ";

    cout << endl;

}