gapi_SobelXY

gapifunctionOpenCV 5.0.0

import { gapi_SobelXY } from '@banou/opencv-wasm'

Use after await initOpenCV(). See the initialization and named imports guide.

ARGUMENTSsrc, ddepth, order, ksize

FUNCTIONgapi_SobelXY

RETURN TYPEtuple_GMat_and_GMat

Call structure. A void return can still write to destination arguments. The parameter descriptions define inputs, outputs and ownership.

Calculates the first, second, third, or mixed image derivatives using an extended Sobel operator.

In all cases except one, the \texttt{ksize} \times \texttt{ksize} separable kernel is used to calculate the derivative. When \texttt{ksize = 1}, the 3 \times 1 or 1 \times 3 kernel is used (that is, no Gaussian smoothing is done). ksize = 1 can only be used for the first or the second x- or y- derivatives.

There is also the special value ksize = FILTER_SCHARR (-1) that corresponds to the 3\times3 Scharr filter that may give more accurate results than the 3\times3 Sobel. The Scharr aperture is

\vecthreethree{-3}{0}{3}{-10}{0}{10}{-3}{0}{3}

for the x-derivative, or transposed for the y-derivative.

The function calculates an image derivative by convolving the image with the appropriate kernel:

\texttt{dst} =  \frac{\partial^{xorder+yorder} \texttt{src}}{\partial x^{xorder} \partial y^{yorder}}

The Sobel operators combine Gaussian smoothing and differentiation, so the result is more or less resistant to the noise. Most often, the function is called with ( xorder = 1, yorder = 0, ksize = 3) or ( xorder = 0, yorder = 1, ksize = 3) to calculate the first x- or y- image derivative. The first case corresponds to a kernel of:

\vecthreethree{-1}{0}{1}{-2}{0}{2}{-1}{0}{1}

The second case corresponds to a kernel of:

\vecthreethree{-1}{-2}{-1}{0}{0}{0}{1}{2}{1}

Note: - First returned matrix correspons to dx derivative while the second one to dy.

Rounding to nearest even is procedeed if hardware supports it, if not - to nearest.
Function textual ID is "org.opencv.imgproc.filters.sobelxy"

See: filter2D, gaussianBlur, cartToPolar

gapi_SobelXY(src: GMat, ddepth: number, order: number, ksize: number, scale: number, delta: number, borderType: number, borderValue: Scalar): tuple_GMat_and_GMat;

6 available overloads

gapi_SobelXY(src: GMat, ddepth: number, order: number): tuple_GMat_and_GMat;

gapi_SobelXY(src: GMat, ddepth: number, order: number, ksize: number): tuple_GMat_and_GMat;

gapi_SobelXY(src: GMat, ddepth: number, order: number, ksize: number, scale: number): tuple_GMat_and_GMat;

gapi_SobelXY(src: GMat, ddepth: number, order: number, ksize: number, scale: number, delta: number): tuple_GMat_and_GMat;

gapi_SobelXY(src: GMat, ddepth: number, order: number, ksize: number, scale: number, delta: number, borderType: number): tuple_GMat_and_GMat;

gapi_SobelXY(src: GMat, ddepth: number, order: number, ksize: number, scale: number, delta: number, borderType: number, borderValue: Scalar): tuple_GMat_and_GMat;

src: input image.
ddepth: output image depth, see filter_depths "combinations"; in the case of 8-bit input images it will result in truncated derivatives.
order: order of the derivatives.
ksize: size of the extended Sobel kernel; it must be odd.
scale: optional scale factor for the computed derivative values; by default, no scaling is applied (see cv::getDerivKernels for details).
delta: optional delta value that is added to the results prior to storing them in dst.
borderType: pixel extrapolation method, see cv::BorderTypes
borderValue: border value in case of constant border type

Returns

The tuple_GMat_and_GMat result.

Upstream declaration ↗

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