@ -1655,7 +1655,7 @@ Initializes a random number generator state.
The function initializes a random number generator and returns the state. The pointer to the state can be then passed to the :ocv:cfunc:`RandInt`, :ocv:cfunc:`RandReal` and :ocv:cfunc:`RandArr` functions. In the current implementation a multiply-with-carry generator is used.
..sealso:: the C++ class :ocv:class:`RNG` replaced ``CvRNG``.
..seealso:: the C++ class :ocv:class:`RNG` replaced ``CvRNG``.
@ -498,8 +498,7 @@ Fills a connected component with the given color.
:param mask:(For the second function only) Operation mask that should be a single-channel 8-bit image, 2 pixels wider and 2 pixels taller. The function uses and updates the mask, so you take responsibility of initializing the ``mask`` content. Flood-filling cannot go across non-zero pixels in the mask. For example, an edge detector output can be used as a mask to stop filling at edges. It is possible to use the same mask in multiple calls to the function to make sure the filled area does not overlap.
..note::
Since the mask is larger than the filled image, a pixel :math:`(x, y)` in ``image`` corresponds to the pixel :math:`(x+1, y+1)` in the ``mask`` .
..note:: Since the mask is larger than the filled image, a pixel :math:`(x, y)` in ``image`` corresponds to the pixel :math:`(x+1, y+1)` in the ``mask`` .
:param seed:Starting point.
@ -782,11 +781,7 @@ should be set to 0's. In the function output, each pixel in
markers is set to a value of the "seed" components or to -1 at
boundaries between the regions.
..note:: Every two neighbor connected
components are not necessarily separated by a watershed boundary (-1's pixels); for
example, when such tangent components exist in the initial
marker image. Visual demonstration and usage example of the function
can be found in the OpenCV samples directory (see the ``watershed.cpp`` demo).
..note:: Every two neighbor connected components are not necessarily separated by a watershed boundary (-1's pixels); for example, when such tangent components exist in the initial marker image. Visual demonstration and usage example of the function can be found in the OpenCV samples directory (see the ``watershed.cpp`` demo).
:math:`\texttt{nu}_{10}=\texttt{mu}_{10}=\texttt{mu}_{01}=\texttt{mu}_{10}=0` , hence the values are not stored.
The moments of a contour are defined in the same way but computed using the Green's formula
(see
http://en.wikipedia.org/wiki/Green_theorem
). So, due to a limited raster resolution, the moments computed for a contour are slightly different from the moments computed for the same rasterized contour.
:math:`\texttt{mu}_{00}=\texttt{m}_{00}`,
:math:`\texttt{nu}_{00}=1`
:math:`\texttt{nu}_{10}=\texttt{mu}_{10}=\texttt{mu}_{01}=\texttt{mu}_{10}=0` , hence the values are not stored.
The moments of a contour are defined in the same way but computed using the Green's formula (see http://en.wikipedia.org/wiki/Green_theorem). So, due to a limited raster resolution, the moments computed for a contour are slightly different from the moments computed for the same rasterized contour.
..seealso::
@ -146,9 +144,7 @@ Finds contours in a binary image.
The function retrieves contours from the binary image using the algorithm
[Suzuki85]_. The contours are a useful tool for shape analysis and object detection and recognition. See ``squares.c`` in the OpenCV sample directory.
..note::
Source ``image`` is modified by this function.
..note:: Source ``image`` is modified by this function.
Vadim Pisarevsky
14 years ago