Developer Reference

  • 2020
  • 07/15/2020
  • Public Content
Contents

ApplyHaarClassifier

Applies a Haar classifier to an image.

Syntax

IppStatus ippiApplyHaarClassifier_32f_C1R(const Ipp32f*
pSrc
, int
srcStep
, const Ipp32f*
pNorm
, int
normStep
, Ipp8u*
pMask
, int
maskStep
, IppiSize
roiSize
, int*
pPositive
, Ipp32f
threshold
, IppiHaarClassifier_32f*
pState
);
IppStatus ippiApplyHaarClassifier_32s32f_C1R(const Ipp32s*
pSrc
, int
srcStep
, const Ipp32f*
pNorm
, int
normStep
, Ipp8u*
pMask
, int
maskStep
, IppiSize
roiSize
, int*
pPositive
, Ipp32f
threshold
, IppiHaarClassifier_32f*
pState
);
IppStatus ippiApplyHaarClassifier_32s_C1RSfs(const Ipp32s*
pSrc
, int
srcStep
, const Ipp32s*
pNorm
, int
normStep
, Ipp8u*
pMask
, int
maskStep
, IppiSize
roiSize
, int*
pPositive
, Ipp32s
threshold
, IppiHaarClassifier_32s*
pState
, int
scaleFactor
);
Include Files
ippcv.h
Domain Dependencies
Headers:
ippcore.h
,
ippvm.h
,
ipps.h
,
ippi.h
Libraries:
ippcore.lib
,
ippvm.lib
,
ipps.lib
,
ippi.lib
Parameters
pSrc
Pointer to the ROI in the source image of integrals.
srcStep
Distance, in bytes, between the starting points of consecutive lines in the source image.
pNorm
Pointer to the ROI in the source image of norm factors.
normStep
Distance, in bytes, between the starting points of consecutive lines in the image of the norm factors.
pMask
Pointer to the source and destination image of classification decisions.
maskStep
Distance, in bytes, between the starting points of consecutive lines in the image of classification decisions.
pPositive
Pointer to the number of positive decisions.
roiSize
Size of the source and destination images ROI in pixels.
threshold
Stage threshold value.
pState
Pointer to the Haar classifier structure.
scaleFactor
Scale factor (see Integer Result Scaling ).
Description
This function operates with ROI (see Regions of Interest in Intel IPP ).
This function applies the Haar classifier to pixels of the source image ROI
pSrc
. The source image should be in the integral representation, it can be obtained by calling one of the integral functions beforehand. The sum of pixels on feature rectangles is computed as:
Here (
y
l
,
x
l
) and (
Y
l
,
X
l
) are coordinates of top left and right bottom pixels of
l
-th rectangle of the feature, and
w
l
is the feature weight. For
i
= 0.
roiSize.height
- 1,
j
= 0.
roiSize.width
- 1 all pixels referred in the above formula should be allocated in memory.
The input value of
pPositive
[0]
is used as a hint to choose the calculation algorithm. If it is greater than or equal to
roiSize.width*roiSize.height
, the value of the classifier is calculated in accordance with the above formula for all pixels of the input image. Otherwise the value of the classifier is calculated for all non-zero pixels of
pMask
image. If the sum is less than
threshold
than the negative decision is made and the value of the corresponding pixel of the
pMask
image is set to zero. The number of positive decisions is assigned to the
pPositive[0]
.
Before using this function, you need to compute the size of the state structure using HaarClassifierGetSize and initialize the structure using HaarClassifierInit or TiltedHaarClassifierInit .
Return Values
ippStsNoErr
Indicates no error.
ippStsNullPtrErr
Indicates an error when one of the specified pointers is
NULL
.
ippStsSizeErr
Indicates an error when
roiSize
has a field with a zero or negative value.
ippStsStepErr
Indicates an error when one of the image step values is less than
roiSize.width
*<
pixelSize
>
.
ippStsNorEvenStepErr
Indicates an error when one of the image step values is not divisible by 4 for 32-bit images.

Product and Performance Information

1

Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

Notice revision #20110804