Returns Gaussian filter coefficients

kernel = cv.getGaussianKernel()
kernel = cv.getGaussianKernel('OptionName', optionValue, ...)

Output

• kernel Output kernel of the specified size and type.

Options

• KSize Aperture size. It should be odd (mod(KSize,2)==1) and positive. default 5.
• 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. default -1.
• KType Type of filter coefficients. It can be single or double. default double.

The function computes and returns the KSize x 1 matrix of Gaussian filter coefficients:

 G_i = alpha * exp( -(i - (KSize-1)/2)^2 / (2*sigma^2) )

where i = 0, ..., KSize-1 and alpha is the scale factor chosen so that \sum_i G_i = 1.

Two of such generated kernels can be passed to cv.sepFilter2D. Those functions automatically recognize smoothing kernels (a symmetrical kernel with sum of weights equal to 1) and handle them accordingly. You may also use the higher-level cv.GaussianBlur