#include <osl_fit_lines.h>

Inheritance diagram for osl_fit_lines:

Public Member Functions
	osl_fit_lines (osl_fit_lines_params const &params, double scale=1.0, double x0=0.0, double y0=0.0)
	~osl_fit_lines ()
void	SetSqrOrMean (bool sm)
void	SetMinFitLength (unsigned int l)
void	SetThreshold (double th)
void	SetTheta (double theta)
void	SetIgnoreEndEdgels (unsigned int ignore)
void	incremental_fit_to_list (vcl_list< osl_edge * > in, vcl_list< osl_edge > *out)
	Method that takes a vcl_list<Edge> that represents the current segmentation and breaks off each Edge for further investigation.
void	simple_fit_to_list (vcl_list< osl_edge * > in, vcl_list< osl_edge > *out)
void	SquareIncrementalFit (vcl_list< osl_edgel_chain * > curves_, osl_edge )
	Method that takes the canny edge data stored in an edge and its associated DigitalCurve, and fits lines using orthogonal regression with mean square error residual and incremental fitting.
void	MeanIncrementalFit (vcl_list< osl_edgel_chain * > curves_, osl_edge )
	This method is used to fit lines incrementally using the mean absolute error instead of the mean square error.
void	OutputLine (vcl_list< osl_edgel_chain * > curves_, int, int, osl_edgel_chain , float)
	Output the fitted line.
void	MergeLines (vcl_list< osl_edgel_chain * > *curves_)
	Takes the top two lines from the vcl_list<ImplicitDigitalLine*> and tests whether a single line fit would satisfy them both.
bool	SanityCheck ()
	Checks that parameters are within acceptable bounds.
Static Public Member Functions
static float	MyGetCost (osl_OrthogRegress const , int, int, osl_edgel_chain )
	This method calculates the current mean absolute cost of fitting a line.
Public Attributes
unsigned int	min_fit_length_
bool	use_square_fit_
double	threshold_
double	theta_
bool	dc_only_
bool	incremtl_
unsigned int	ignore_end_edgels_
Private Attributes
osl_OrthogRegress *	data_
int	old_finish_

Detailed Description

Definition at line 51 of file osl_fit_lines.h.

Constructor & Destructor Documentation

osl_fit_lines::osl_fit_lines	(	osl_fit_lines_params const &	params,
		double	scale = `1.0`,
		double	x0 = `0.0`,
		double	y0 = `0.0`
	)

Definition at line 22 of file osl_fit_lines.cxx.

osl_fit_lines::~osl_fit_lines ( )

Definition at line 32 of file osl_fit_lines.cxx.

Member Function Documentation

void osl_fit_lines::incremental_fit_to_list	(	vcl_list< osl_edge * > *	myedges,
		vcl_list< osl_edge * > *	outedges
	)

Method that takes a vcl_list<Edge*>* that represents the current segmentation and breaks off each Edge for further investigation.

An incremental fitting process is applied to the osl_edgel_chain in each osl_edge. The resultant segmentation is then written to output (with edges destroyed).

Definition at line 130 of file osl_fit_lines.cxx.

void osl_fit_lines::MeanIncrementalFit	(	vcl_list< osl_edgel_chain * > *	curves_,
		osl_edge *	edge
	)

This method is used to fit lines incrementally using the mean absolute error instead of the mean square error.

The difference between this and SquareIncrementalFit is very small.

Definition at line 202 of file osl_fit_lines.cxx.

void osl_fit_lines::MergeLines ( vcl_list< osl_edgel_chain * > * curves_ )

Takes the top two lines from the vcl_list<ImplicitDigitalLine*> and tests whether a single line fit would satisfy them both.

The process involves fitting a single line to the other two lines by minimising the integral of the Euclidean distance between the lines. If the lines appear to come from the same line, a refit should be done using the underlying edgel data, *** BUT THIS IS NOT YET IMPLEMENTED ***

Definition at line 569 of file osl_fit_lines.cxx.

float osl_fit_lines::MyGetCost	(	osl_OrthogRegress const *	fitter,
		int	start,
		int	finish,
		osl_edgel_chain *	dc
	)		`[static]`

This method calculates the current mean absolute cost of fitting a line.

Definition at line 837 of file osl_fit_lines.cxx.

void osl_fit_lines::OutputLine	(	vcl_list< osl_edgel_chain * > *	curves_,
		int	start,
		int	finish,
		osl_edgel_chain *	dc,
		float
	)

Output the fitted line.

Definition at line 523 of file osl_fit_lines.cxx.

bool osl_fit_lines_params::SanityCheck ( ) [inherited]

Checks that parameters are within acceptable bounds.

Definition at line 23 of file osl_fit_lines_params.cxx.

void osl_fit_lines::SetIgnoreEndEdgels ( unsigned int ignore ) [inline]

Definition at line 61 of file osl_fit_lines.h.

void osl_fit_lines::SetMinFitLength ( unsigned int l ) [inline]

Definition at line 58 of file osl_fit_lines.h.

void osl_fit_lines::SetSqrOrMean ( bool sm ) [inline]

Definition at line 57 of file osl_fit_lines.h.

void osl_fit_lines::SetTheta ( double theta ) [inline]

Definition at line 60 of file osl_fit_lines.h.

void osl_fit_lines::SetThreshold ( double th ) [inline]

Definition at line 59 of file osl_fit_lines.h.

void osl_fit_lines::simple_fit_to_list	(	vcl_list< osl_edge * > *	in,
		vcl_list< osl_edge * > *	out
	)

Definition at line 47 of file osl_fit_lines.cxx.

void osl_fit_lines::SquareIncrementalFit	(	vcl_list< osl_edgel_chain * > *	curves_,
		osl_edge *	edge
	)

Method that takes the canny edge data stored in an edge and its associated DigitalCurve, and fits lines using orthogonal regression with mean square error residual and incremental fitting.

Definition at line 377 of file osl_fit_lines.cxx.