SIFT.hpp File Reference

#include "opencv2/imgproc.hpp"
#include "opencv2/core.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/xfeatures2d.hpp"
#include <vector>
#include <chrono>

Macros
#define	SIFT_INTERVALS   3
#define	SIFT_SIGMA   1.6f
#define	SIFT_CONTRAST_THRES   0.03
#define	SIFT_CURVATURE_THRES   10
#define	SIFT_IMG_DBL   false
#define	SIFT_DESCR_WIDTH   4
#define	SIFT_DESCR_HIST_BINS   8
#define	STATUS_BAR   true

Functions
void	extractSiftFeatures (const Mat &img, vector< KeyPoint > &keypoints, Mat &descriptor, int intervals=SIFT_INTERVALS, double sigma=SIFT_SIGMA, double contrast_thres=SIFT_CONTRAST_THRES, int curvature_thres=SIFT_CURVATURE_THRES, bool img_dbl=SIFT_IMG_DBL, int descr_width=SIFT_DESCR_WIDTH, int descr_hist_bins=SIFT_DESCR_HIST_BINS)
void	convertGrayAndNormalize (const Mat &input, Mat &output)
void	resizeHalf (const Mat &input, Mat &output, Size outSize)
void	filterCreation (double **GKernel, int kSize, double sigma)
void	filterCreation1D (float *GKernel, int kSize, double sigma)
void	gaussianBlur (const Mat &src, Mat &output, int kSize, double **kernel)
void	start_time (system_clock::time_point &startTime)
void	end_time (system_clock::time_point &startTime, system_clock::time_point &endTime, const char *step_name)
void	statusBarUpdate (Mat &part, Mat &totalResult, int idx, int portion, bool is_left)

Variables
std::chrono::duration< double >	global_elapsed_Time [4]
double **	gKernel
int	kSize
Mat	totalResult
Mat	partM [6]
bool	is_left

Macro Definition Documentation

SIFT_CONTRAST_THRES

#define SIFT_CONTRAST_THRES   0.03

SIFT_CURVATURE_THRES

#define SIFT_CURVATURE_THRES   10

SIFT_DESCR_HIST_BINS

#define SIFT_DESCR_HIST_BINS   8

SIFT_DESCR_WIDTH

#define SIFT_DESCR_WIDTH   4

SIFT_IMG_DBL

#define SIFT_IMG_DBL   false

SIFT_INTERVALS

#define SIFT_INTERVALS   3

DEFAULT SIFT PARAMS

SIFT_SIGMA

#define SIFT_SIGMA   1.6f

STATUS_BAR

#define STATUS_BAR   true

Function Documentation

convertGrayAndNormalize()

void convertGrayAndNormalize	(	const Mat &	input,
		Mat &	output
	)

Change 3Channel RGB image to normalized gray image.

Parameters

input	3Channel RGB input image
output	normalized grayscale output image with pixel values in 0.0f~1.0f

end_time()

void end_time	(	system_clock::time_point &	startTime,
		system_clock::time_point &	endTime,
		const char *	step_name
	)

extractSiftFeatures()

void extractSiftFeatures	(	const Mat &	img,
		vector< KeyPoint > &	keypoints,
		Mat &	descriptor,
		int	intervals = SIFT_INTERVALS,
		double	sigma = SIFT_SIGMA,
		double	contrast_thres = SIFT_CONTRAST_THRES,
		int	curvature_thres = SIFT_CURVATURE_THRES,
		bool	img_dbl = SIFT_IMG_DBL,
		int	descr_width = SIFT_DESCR_WIDTH,
		int	descr_hist_bins = SIFT_DESCR_HIST_BINS
	)

[Detect & extract sift features for an image]

Parameters

img	[source image for extract sift features : grayscale image with pixel values in 0.0f~1.0f]
keypoints	[vector for store sift feature point]
descriptor	[Mat for store sift descriptor, each row for a keypoint]
intervals	[the number of sampled intervals per octave]
sigma	[sigma for initial gaussian smoothing]
contrast_thres	[threshold on keypoint contrast]
curvature_thres	[threshold on keypoint ratio of principle curvatures]
img_dbl	[double image size before pyramid construction?]
descr_width	[width of descriptor histogram array]
descr_hist_bins	[number of bins per histogram in descriptor array]

filterCreation()

void filterCreation	(	double **	GKernel,
		int	kSize,
		double	sigma
	)

Create 2D gaussian filter

Parameters

GKernel	output 2D gaussian filter
kSize	gaussian kernel size
sigma	gaussian sigma

filterCreation1D()

void filterCreation1D	(	float *	GKernel,
		int	kSize,
		double	sigma
	)

Create 1D gaussian filter

Parameters

GKernel	output 1D gaussian filter
kSize	gaussian kernel size
sigma	gaussian sigma

gaussianBlur()

void gaussianBlur	(	const Mat &	src,
		Mat &	output,
		int	kSize,
		double **	kernel
	)

Blurs an image using a Gaussian filter using padding
Assume that dst already copy the data of src

Parameters

src	input image; Normalized grayscale input image
output	output image of the same size and type as src.
kSize	width of the input image
kernel	Gaussian 2D kernel

resizeHalf()

void resizeHalf	(	const Mat &	input,
		Mat &	output,
		Size	outSize
	)

Resize image using Nearest neighbor sampling. Reduce width and height in half. (Native)

Parameters

input	normalized grayscale input image
output	resized output image
outSize	output image size

start_time()

void start_time

(

system_clock::time_point &

startTime

)

statusBarUpdate()

void statusBarUpdate	(	Mat &	part,
		Mat &	totalResult,
		int	idx,
		int	portion,
		bool	is_left
	)

Variable Documentation

gKernel

double** gKernel

extern

global_elapsed_Time

std::chrono::duration<double> global_elapsed_Time[4]

extern

is_left

bool is_left

extern

kSize

int kSize

extern

partM

Mat partM[6]

extern

totalResult

Mat totalResult

extern