#include <gevd_fold.h>

Public Member Functions
	gevd_fold (float smooth_sigma=1, float noise_sigma=-0.5, float contour_factor=1.0, float junction_factor=1.5)
	Save parameters and create workspace for detecting fold profiles.
	~gevd_fold ()
	Free space allocated for detecting fold profiles. Does nothing.
bool	DetectEdgels (const gevd_bufferxy &image, gevd_bufferxy &edgels, gevd_bufferxy &direction, gevd_bufferxy &locationx, gevd_bufferxy &locationy, bool peaks_only=false, bool valleys_only=false, bool transfer=false, gevd_bufferxy &mag=null_bufferxy, gevd_bufferxy &angle=null_bufferxy)
	Detect fold profiles with ddG edge detector.
int	RecoverJunctions (const gevd_bufferxy &image, gevd_bufferxy &edgels, gevd_bufferxy &direction, gevd_bufferxy &locationx, gevd_bufferxy &locationy, int &junctionx, int &junctiony)
	Find junctions by searching for extensions of contours from their dangling end points.
float	NoiseSigma () const
	query stored/estimated noise sigma.
float	NoiseResponse () const
	response of noise sigma to filter ddG.
float	NoiseThreshold (bool shortp=false) const
	elongated/directional?.
Static Public Member Functions
static float	NoiseResponseToFilter (float noiseSigma, float smoothSigma, float filterFactor)
	Compute response of white noise through the filter ddG, or second-derivative of the Gaussian.
Static Public Attributes
static gevd_bufferxy *	null_bufferxy = 0
Protected Attributes
float	smoothSigma
	spatial smoothing
float	noiseSigma
	sensor/texture noise
float	contourFactor
float	junctionFactor
	threshold factor for edgels
float	filterFactor
	factor in convolution filter
Friends
vcl_ostream &	operator<< (vcl_ostream &os, const gevd_fold &st)
	Output a snapshot of current control parameters.
vcl_ostream &	operator<< (vcl_ostream &os, gevd_fold &st)
	Output a snapshot of current control parameters.

Detailed Description

Definition at line 65 of file gevd_fold.h.

Constructor & Destructor Documentation

gevd_fold::gevd_fold	(	float	smooth_sigma = `1`,
		float	noise_sigma = `-0.5`,
		float	contour_factor = `1.0`,
		float	junction_factor = `1.5`
	)

Save parameters and create workspace for detecting fold profiles.

High frequency features are smoothed away by smooth_sigma. Texture or white noise less than noise_sigma are not detected. smooth_sigma = 0.5-2.0, 1.0 insures separation of independent folds >= 2. noise_sigma = is standard deviation of intensity, in a uniform region. Optionally estimate sensor/texture sigma, if given noise sigma is a negative factor -k between -[0 1]. In this case, noise_sigma = (1-k)*sensor_sigma + k*texture_sigma. Response of white noise to the filter ddG is computed, and then multiplied by contour_factor/junction_factor to obtain thresholds for detecting contour/junction edges. threshold factor for junction edgels

Parameters:

smooth_sigma	spatial smoothing [0.5 2.0]
noise_sigma	sensor/texture intensity noise -[0 1]
contour_factor	threshold factor for contour edgels

Definition at line 34 of file gevd_fold.cxx.

gevd_fold::~gevd_fold ( ) [inline]

Free space allocated for detecting fold profiles. Does nothing.

Definition at line 86 of file gevd_fold.h.

Member Function Documentation

bool gevd_fold::DetectEdgels	(	const gevd_bufferxy &	image,
		gevd_bufferxy *&	edgels,
		gevd_bufferxy *&	direction,
		gevd_bufferxy *&	locationx,
		gevd_bufferxy *&	locationy,
		bool	peaks_only = `false`,
		bool	valleys_only = `false`,
		bool	transfer = `false`,
		gevd_bufferxy *&	mag = `null_bufferxy`,
		gevd_bufferxy *&	angle = `null_bufferxy`
	)

Detect fold profiles with ddG edge detector.

The image is convolved with a Gaussian to smooth away high frequency noise, and insure separation of fold responses. Then the largest absolute eigenvalue, and corresponding eigenvector of the local Hessian are computed using second difference [+1 -2 +1]. Optionally estimate sensor/texture sigma and set threshold. Finally, non maximum suppression is done to find strict local maxima of curvature. The edge detector finds elongated contours only. These contours are typically broken at junctions because non maximum suppression is done along only the strongest direction. Return contour (float), direction (byte), location (float) images. Return true if no exception. J. Canny, A Computational Approach to Edge Detection, IEEE Trans on PAMI, vol 8, no 6, Nov 1986.

Parameters:

image	float image
edgels	strength = dG * I
direction	direction % PI/4
locationx	subpixel loc

Definition at line 58 of file gevd_fold.cxx.

float gevd_fold::NoiseResponse ( ) const

response of noise sigma to filter ddG.

Compute response of white noise through the filter ddG, or second-derivative of the Gaussian. Using a threshold of 3 times this noise response would eliminate 99% of the noise edges.

Definition at line 395 of file gevd_fold.cxx.

float gevd_fold::NoiseResponseToFilter	(	float	noiseSigma,
		float	smoothSigma,
		float	filterFactor
	)		`[static]`

Compute response of white noise through the filter ddG, or second-derivative of the Gaussian.

Using a threshold of 3 times this noise response would eliminate 99% of the noise edges.

Definition at line 413 of file gevd_fold.cxx.

float gevd_fold::NoiseSigma ( ) const

query stored/estimated noise sigma.

Return the standard deviation of raw noise, in the original image, either estimated or given by the user. If the noise has not been estimated, return 0.

Definition at line 388 of file gevd_fold.cxx.

float gevd_fold::NoiseThreshold ( bool shortp = false ) const

elongated/directional?.

Return threshold for detecting contour or junction, which is response of white gaussian noise, noise_sigma, to fold edge detector, i.e. second-order derivative of Gaussian, smooth_sigma. noise_sigma can be estimated by finding the standard deviation in a region of constant intensity, and no texture patterns. Use short_factor*noise_sigma and smooth_sigma/2, when detecting junctions, to account for multiple responses to fold edge detector.

Definition at line 403 of file gevd_fold.cxx.

int gevd_fold::RecoverJunctions	(	const gevd_bufferxy &	image,
		gevd_bufferxy &	edgels,
		gevd_bufferxy &	direction,
		gevd_bufferxy &	locationx,
		gevd_bufferxy &	locationy,
		int *&	junctionx,
		int *&	junctiony
	)

Find junctions by searching for extensions of contours from their dangling end points.

Non maximum suppression insures that contours have width < 2, and so we can find the left/right neighbors, and deduce end points. By using a minimally smoothed image, we find fold profiles up to joining with a stronger contour, thus recovering the missing junction caused by NMS along only 1 direction. The junctions are returned but are not set in the contour image, to prevent incorrect tracing of stronger contours first.

Parameters: