mirror of
https://github.com/opencv/opencv.git
synced 2024-11-26 04:00:30 +08:00
96 lines
3.6 KiB
ReStructuredText
96 lines
3.6 KiB
ReStructuredText
Histograms
|
|
==========
|
|
|
|
.. highlight:: cpp
|
|
|
|
|
|
|
|
CalcPGH
|
|
-------
|
|
Calculates a pair-wise geometrical histogram for a contour.
|
|
|
|
.. ocv:cfunction:: void cvCalcPGH( const CvSeq* contour, CvHistogram* hist )
|
|
|
|
:param contour: Input contour. Currently, only integer point coordinates are allowed.
|
|
|
|
:param hist: Calculated histogram. It must be two-dimensional.
|
|
|
|
The function calculates a 2D pair-wise geometrical histogram (PGH), described in [Iivarinen97]_ for the contour. The algorithm considers every pair of contour
|
|
edges. The angle between the edges and the minimum/maximum distances
|
|
are determined for every pair. To do this, each of the edges in turn
|
|
is taken as the base, while the function loops through all the other
|
|
edges. When the base edge and any other edge are considered, the minimum
|
|
and maximum distances from the points on the non-base edge and line of
|
|
the base edge are selected. The angle between the edges defines the row
|
|
of the histogram in which all the bins that correspond to the distance
|
|
between the calculated minimum and maximum distances are incremented
|
|
(that is, the histogram is transposed relatively to the definition in the original paper). The histogram can be used for contour matching.
|
|
|
|
|
|
.. [Iivarinen97] Jukka Iivarinen, Markus Peura, Jaakko Srel, and Ari Visa. *Comparison of Combined Shape Descriptors for Irregular Objects*, 8th British Machine Vision Conference, BMVC'97. http://www.cis.hut.fi/research/IA/paper/publications/bmvc97/bmvc97.html
|
|
|
|
|
|
QueryHistValue*D
|
|
----------------
|
|
Queries the value of the histogram bin.
|
|
|
|
.. ocv:cfunction:: float cvQueryHistValue_1D(CvHistogram hist, int idx0)
|
|
.. ocv:cfunction:: float cvQueryHistValue_2D(CvHistogram hist, int idx0, int idx1)
|
|
.. ocv:cfunction:: float cvQueryHistValue_3D(CvHistogram hist, int idx0, int idx1, int idx2)
|
|
.. ocv:cfunction:: float cvQueryHistValue_nD(CvHistogram hist, const int* idx)
|
|
|
|
.. ocv:pyoldfunction:: cv.QueryHistValue_1D(hist, idx0) -> float
|
|
.. ocv:pyoldfunction:: cv.QueryHistValue_2D(hist, idx0, idx1) -> float
|
|
.. ocv:pyoldfunction:: cv.QueryHistValue_3D(hist, idx0, idx1, idx2) -> float
|
|
.. ocv:pyoldfunction:: cv.QueryHistValue_nD(hist, idx) -> float
|
|
|
|
:param hist: Histogram.
|
|
|
|
:param idx0: 0-th index.
|
|
|
|
:param idx1: 1-st index.
|
|
|
|
:param idx2: 2-nd index.
|
|
|
|
:param idx: Array of indices.
|
|
|
|
The macros return the value of the specified bin of the 1D, 2D, 3D, or N-D histogram. In case of a sparse histogram, the function returns 0. If the bin is not present in the histogram, no new bin is created.
|
|
|
|
GetHistValue\_?D
|
|
----------------
|
|
Returns a pointer to the histogram bin.
|
|
|
|
.. ocv:cfunction:: float cvGetHistValue_1D(CvHistogram hist, int idx0)
|
|
|
|
.. ocv:cfunction:: float cvGetHistValue_2D(CvHistogram hist, int idx0, int idx1)
|
|
|
|
.. ocv:cfunction:: float cvGetHistValue_3D(CvHistogram hist, int idx0, int idx1, int idx2)
|
|
|
|
.. ocv:cfunction:: float cvGetHistValue_nD(CvHistogram hist, int idx)
|
|
|
|
:param hist: Histogram.
|
|
|
|
:param idx0: 0-th index.
|
|
|
|
:param idx1: 1-st index.
|
|
|
|
:param idx2: 2-nd index.
|
|
|
|
:param idx: Array of indices.
|
|
|
|
::
|
|
|
|
#define cvGetHistValue_1D( hist, idx0 )
|
|
((float*)(cvPtr1D( (hist)->bins, (idx0), 0 ))
|
|
#define cvGetHistValue_2D( hist, idx0, idx1 )
|
|
((float*)(cvPtr2D( (hist)->bins, (idx0), (idx1), 0 )))
|
|
#define cvGetHistValue_3D( hist, idx0, idx1, idx2 )
|
|
((float*)(cvPtr3D( (hist)->bins, (idx0), (idx1), (idx2), 0 )))
|
|
#define cvGetHistValue_nD( hist, idx )
|
|
((float*)(cvPtrND( (hist)->bins, (idx), 0 )))
|
|
|
|
..
|
|
|
|
The macros ``GetHistValue`` return a pointer to the specified bin of the 1D, 2D, 3D, or N-D histogram. In case of a sparse histogram, the function creates a new bin and sets it to 0, unless it exists already.
|
|
|