#include <sift.hpp>

Public Member Functions
	Sift (u16_t dogsPerEpoch=3, u16_t octaves=3, f32_t sigma=1.6, f32_t k=std::sqrt(2), bool subpixel=false)

std::vector< InterestPoint >	calculate (vigra::MultiArray< 2, f32_t > &)

Public Attributes
const bool	subpixel

Private Member Functions
void	_createDecriptors (std::vector< InterestPoint > &)

std::vector< f32_t >	_eliminateVectorThreshold (std::vector< f32_t > &) const

void	_createMagnitudePyramid ()

void	_createOrientationPyramid ()

void	_eliminateEdgeResponses (std::vector< InterestPoint > &, const Matrix< OctaveElem > &) const

const std::set< f32_t >	_findPeaks (const std::array< f32_t, 36 > &) const

void	_orientationAssignment (std::vector< InterestPoint > &)

const Point< u16_t, u16_t >	_findNearestGaussian (f32_t)

void	_findScaleSpaceExtrema (const Matrix< OctaveElem > &, std::vector< InterestPoint > &) const

const Matrix< OctaveElem >	_createDOGs (vigra::MultiArray< 2, f32_t > &)

Private Attributes
const f32_t	_sigma

const f32_t	_k

const u16_t	_dogsPerEpoch

const u16_t	_octaves

Matrix< OctaveElem >	_gaussians

Matrix< vigra::MultiArray< 2, f32_t > >	_magnitudes

Matrix< vigra::MultiArray< 2, f32_t > >	_orientations

Constructor & Destructor Documentation

sift::Sift::Sift	(	u16_t	dogsPerEpoch = `3`,
		u16_t	octaves = `3`,
		f32_t	sigma = `1.6`,
		f32_t	k = `std::sqrt(2)`,
		bool	subpixel = `false`
	)

inlineexplicit

Parameters

sigma	standard value 1.6
k	standard value square root of 2
dogsPerEpoch	How many DOGs should be created per octave
octaves	how many octaves should be calculated
subpixel	wether the calculation is based on subpixel basis or not

Member Function Documentation

void sift::Sift::_createDecriptors ( std::vector< InterestPoint > & interestPoints )

private

Creates the local image desciptors.

Parameters

interestpoints the vector with interestpoints

const Matrix< OctaveElem > sift::Sift::_createDOGs ( vigra::MultiArray< 2, f32_t > & img )

private

Creates the Difference of Gaussians for the count of octaves.

Parameters

img	the given img

Returns: a matrix with the octaves as width and octave elements as height, which contain the DoGs

void sift::Sift::_createMagnitudePyramid ( )

private

Creates magnitude versions of all the gaussian images.

void sift::Sift::_createOrientationPyramid ( )

private

Create orientation versions of all the gaussian images.

void sift::Sift::_eliminateEdgeResponses	(	std::vector< InterestPoint > &	interestPoints,
		const Matrix< OctaveElem > &	dogs
	)		const

private

Keypoint Location using Taylor expansion to filter the weak interest points. Those interest points, which get filtered get their filtered flag set to true

Parameters

interestpoints	the vector with interestpoints
dogs	the dogs which were calculated in an earlier step

std::vector< f32_t > sift::Sift::_eliminateVectorThreshold ( std::vector< f32_t > & vec ) const

private

Eliminates all values above the threshold of 0.2 and performs a new vector normalization as long as there are no more values above 0.2

Parameters

vec	The given vector

const Point< u16_t, u16_t > sift::Sift::_findNearestGaussian ( f32_t scale )

private

Finds the nearest gaussian, based on the scale given

Parameters

scale the scale

Returns: the point where the Gaussian is lying in the pyramid

const std::set< f32_t > sift::Sift::_findPeaks ( const std::array< f32_t, 36 > & histo ) const

private

Searches for the highest Element in the orientation histogram and searches for other orientations within a 80% range. Everything outside the range will be set to -1.

Parameters

histo The given histogram on which the peak calculation finds place

Returns: an array with 36 elements, standing for the 36 bins of orientation possibilities

void sift::Sift::_findScaleSpaceExtrema	(	const Matrix< OctaveElem > &	dogs,
		std::vector< InterestPoint > &	interestPoints
	)		const

private

Finds the Scale space extrema aka InterestPoints

Parameters

dogs	a matrix of DOGs
interestPoints	a vector which holds interestPoints. Will be filled with the found interest points

void sift::Sift::_orientationAssignment ( std::vector< InterestPoint > & interestPoints )

private

Calculates the orientation assignments for the interestPoints

Parameters

interestPoints the found interestPoints for whom the orientation should be calulated

std::vector< InterestPoint > sift::Sift::calculate ( vigra::MultiArray< 2, f32_t > & img )

Processes the whole Sift calculation

Parameters

img	the given image

Returns: a vector containing the filtered sift features

Member Data Documentation

const u16_t sift::Sift::_dogsPerEpoch

private

How many DoGs will be calculated per epoch. Minimum is 3.

Matrix<OctaveElem> sift::Sift::_gaussians

private

The Gaussians calculated during the algorithm.

const f32_t sift::Sift::_k

private

The constant which is multiplied with sigma to get the Gaussians and DoGs.

Matrix<vigra::MultiArray<2, f32_t> > sift::Sift::_magnitudes

private

The magnitudes of the gaussians

const u16_t sift::Sift::_octaves

private

How many octaves of DoGs will be calculated.

Matrix<vigra::MultiArray<2, f32_t> > sift::Sift::_orientations

private

The orientations of the gaussians

const f32_t sift::Sift::_sigma

private

The sigma value is used for the standard derivation of the Gaussian calculations.

const bool sift::Sift::subpixel

Wether to process the algorithm based on subpixel basis or not

The documentation for this class was generated from the following files:

Public Member Functions

Public Attributes

Private Member Functions

Private Attributes

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation