mirror of
https://github.com/opencv/opencv.git
synced 2024-12-11 22:59:16 +08:00
174 lines
7.7 KiB
ReStructuredText
174 lines
7.7 KiB
ReStructuredText
Feature Detection and Description
|
|
=================================
|
|
|
|
SIFT
|
|
----
|
|
.. ocv:class:: SIFT
|
|
|
|
Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) approach. ::
|
|
|
|
class CV_EXPORTS SIFT
|
|
{
|
|
public:
|
|
struct CommonParams
|
|
{
|
|
static const int DEFAULT_NOCTAVES = 4;
|
|
static const int DEFAULT_NOCTAVE_LAYERS = 3;
|
|
static const int DEFAULT_FIRST_OCTAVE = -1;
|
|
enum{ FIRST_ANGLE = 0, AVERAGE_ANGLE = 1 };
|
|
|
|
CommonParams();
|
|
CommonParams( int _nOctaves, int _nOctaveLayers, int _firstOctave,
|
|
int _angleMode );
|
|
int nOctaves, nOctaveLayers, firstOctave;
|
|
int angleMode;
|
|
};
|
|
|
|
struct DetectorParams
|
|
{
|
|
static double GET_DEFAULT_THRESHOLD()
|
|
{ return 0.04 / SIFT::CommonParams::DEFAULT_NOCTAVE_LAYERS / 2.0; }
|
|
static double GET_DEFAULT_EDGE_THRESHOLD() { return 10.0; }
|
|
|
|
DetectorParams();
|
|
DetectorParams( double _threshold, double _edgeThreshold );
|
|
double threshold, edgeThreshold;
|
|
};
|
|
|
|
struct DescriptorParams
|
|
{
|
|
static double GET_DEFAULT_MAGNIFICATION() { return 3.0; }
|
|
static const bool DEFAULT_IS_NORMALIZE = true;
|
|
static const int DESCRIPTOR_SIZE = 128;
|
|
|
|
DescriptorParams();
|
|
DescriptorParams( double _magnification, bool _isNormalize,
|
|
bool _recalculateAngles );
|
|
double magnification;
|
|
bool isNormalize;
|
|
bool recalculateAngles;
|
|
};
|
|
|
|
SIFT();
|
|
//! sift-detector constructor
|
|
SIFT( double _threshold, double _edgeThreshold,
|
|
int _nOctaves=CommonParams::DEFAULT_NOCTAVES,
|
|
int _nOctaveLayers=CommonParams::DEFAULT_NOCTAVE_LAYERS,
|
|
int _firstOctave=CommonParams::DEFAULT_FIRST_OCTAVE,
|
|
int _angleMode=CommonParams::FIRST_ANGLE );
|
|
//! sift-descriptor constructor
|
|
SIFT( double _magnification, bool _isNormalize=true,
|
|
bool _recalculateAngles = true,
|
|
int _nOctaves=CommonParams::DEFAULT_NOCTAVES,
|
|
int _nOctaveLayers=CommonParams::DEFAULT_NOCTAVE_LAYERS,
|
|
int _firstOctave=CommonParams::DEFAULT_FIRST_OCTAVE,
|
|
int _angleMode=CommonParams::FIRST_ANGLE );
|
|
SIFT( const CommonParams& _commParams,
|
|
const DetectorParams& _detectorParams = DetectorParams(),
|
|
const DescriptorParams& _descriptorParams = DescriptorParams() );
|
|
|
|
//! returns the descriptor size in floats (128)
|
|
int descriptorSize() const { return DescriptorParams::DESCRIPTOR_SIZE; }
|
|
//! finds the keypoints using the SIFT algorithm
|
|
void operator()(const Mat& img, const Mat& mask,
|
|
vector<KeyPoint>& keypoints) const;
|
|
//! finds the keypoints and computes descriptors for them using SIFT algorithm.
|
|
//! Optionally it can compute descriptors for the user-provided keypoints
|
|
void operator()(const Mat& img, const Mat& mask,
|
|
vector<KeyPoint>& keypoints,
|
|
Mat& descriptors,
|
|
bool useProvidedKeypoints=false) const;
|
|
|
|
CommonParams getCommonParams () const { return commParams; }
|
|
DetectorParams getDetectorParams () const { return detectorParams; }
|
|
DescriptorParams getDescriptorParams () const { return descriptorParams; }
|
|
protected:
|
|
...
|
|
};
|
|
|
|
|
|
|
|
|
|
SURF
|
|
----
|
|
.. ocv:class:: SURF
|
|
|
|
Class for extracting Speeded Up Robust Features from an image [Bay06]_. The class is derived from ``CvSURFParams`` structure, which specifies the algorithm parameters:
|
|
|
|
.. ocv:member:: int extended
|
|
|
|
* 0 means that the basic descriptors (64 elements each) shall be computed
|
|
* 1 means that the extended descriptors (128 elements each) shall be computed
|
|
|
|
.. ocv:member:: int upright
|
|
|
|
* 0 means that detector computes orientation of each feature.
|
|
* 1 means that the orientation is not computed (which is much, much faster). For example, if you match images from a stereo pair, or do image stitching, the matched features likely have very similar angles, and you can speed up feature extraction by setting ``upright=1``.
|
|
|
|
.. ocv:member:: double hessianThreshold
|
|
|
|
Threshold for the keypoint detector. Only features, whose hessian is larger than ``hessianThreshold`` are retained by the detector. Therefore, the larger the value, the less keypoints you will get. A good default value could be from 300 to 500, depending from the image contrast.
|
|
|
|
.. ocv:member:: int nOctaves
|
|
|
|
The number of a gaussian pyramid octaves that the detector uses. It is set to 4 by default. If you want to get very large features, use the larger value. If you want just small features, decrease it.
|
|
|
|
.. ocv:member:: int nOctaveLayers
|
|
|
|
The number of images within each octave of a gaussian pyramid. It is set to 2 by default.
|
|
|
|
|
|
.. [Bay06] Bay, H. and Tuytelaars, T. and Van Gool, L. "SURF: Speeded Up Robust Features", 9th European Conference on Computer Vision, 2006
|
|
|
|
|
|
SURF::SURF
|
|
----------
|
|
The SURF extractor constructors.
|
|
|
|
.. ocv:function:: SURF::SURF()
|
|
|
|
.. ocv:function:: SURF::SURF(double hessianThreshold, int nOctaves=4, int nOctaveLayers=2, bool extended=false, bool upright=false)
|
|
|
|
.. ocv:pyfunction:: cv2.SURF(_hessianThreshold[, _nOctaves[, _nOctaveLayers[, _extended[, _upright]]]]) -> <SURF object>
|
|
|
|
:param hessianThreshold: Threshold for hessian keypoint detector used in SURF.
|
|
|
|
:param nOctaves: Number of pyramid octaves the keypoint detector will use.
|
|
|
|
:param nOctaveLayers: Number of octave layers within each octave.
|
|
|
|
:param extended: Extended descriptor flag (true - use extended 128-element descriptors; false - use 64-element descriptors).
|
|
|
|
:param upright: Up-right or rotated features flag (true - do not compute orientation of features; false - compute orientation).
|
|
|
|
|
|
SURF::operator()
|
|
----------------
|
|
Detects keypoints and computes SURF descriptors for them.
|
|
|
|
.. ocv:function:: void SURF::operator()(const Mat& image, const Mat& mask, vector<KeyPoint>& keypoints)
|
|
.. ocv:function:: void SURF::operator()(const Mat& image, const Mat& mask, vector<KeyPoint>& keypoints, vector<float>& descriptors, bool useProvidedKeypoints=false)
|
|
|
|
.. ocv:pyfunction:: cv2.SURF.detect(img, mask) -> keypoints
|
|
.. ocv:pyfunction:: cv2.SURF.detect(img, mask[, useProvidedKeypoints]) -> keypoints, descriptors
|
|
|
|
.. ocv:cfunction:: void cvExtractSURF( const CvArr* image, const CvArr* mask, CvSeq** keypoints, CvSeq** descriptors, CvMemStorage* storage, CvSURFParams params )
|
|
|
|
.. ocv:pyoldfunction:: cv.ExtractSURF(image, mask, storage, params)-> (keypoints, descriptors)
|
|
|
|
:param image: Input 8-bit grayscale image
|
|
|
|
:param mask: Optional input mask that marks the regions where we should detect features.
|
|
|
|
:param keypoints: The input/output vector of keypoints
|
|
|
|
:param descriptors: The output concatenated vectors of descriptors. Each descriptor is 64- or 128-element vector, as returned by ``SURF::descriptorSize()``. So the total size of ``descriptors`` will be ``keypoints.size()*descriptorSize()``.
|
|
|
|
:param useProvidedKeypoints: Boolean flag. If it is true, the keypoint detector is not run. Instead, the provided vector of keypoints is used and the algorithm just computes their descriptors.
|
|
|
|
:param storage: Memory storage for the output keypoints and descriptors in OpenCV 1.x API.
|
|
|
|
:param params: SURF algorithm parameters in OpenCV 1.x API.
|
|
|
|
The function is parallelized with the TBB library.
|