lti::colorEdgesGS::parameters Class Reference

the parameters for the class colorEdgesGS More...

#include <ltiColorEdgesGS.h>

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List of all members.

Public Member Functions
	parameters ()
	parameters (const parameters &other)
	~parameters ()
const char *	getTypeName () const
parameters &	copy (const parameters &other)
parameters &	operator= (const parameters &other)
virtual functor::parameters *	clone () const
virtual bool	write (ioHandler &handler, const bool complete=true) const
virtual bool	read (ioHandler &handler, const bool complete=true)
bool	measureNoise (const image &img, const rectangle &window=rectangle(0, 0, std::numeric_limits< int >::max(), std::numeric_limits< int >::max()))
Public Attributes
ubyte	shadowEdgeValue
ubyte	highlightEdgeValue
trgbPixel< float >	noiseStdDeviation
gradientFunctor::parameters	gradient
float	uncertaintyFactor

Detailed Description

the parameters for the class colorEdgesGS

Constructor & Destructor Documentation

lti::colorEdgesGS::parameters::parameters ( )

default constructor

Reimplemented from lti::edgeDetector::parameters.

lti::colorEdgesGS::parameters::parameters ( const parameters & other )

copy constructor

Parameters:

other

the parameters object to be copied

Reimplemented from lti::edgeDetector::parameters.

lti::colorEdgesGS::parameters::~parameters ( ) [virtual]

destructor

Reimplemented from lti::edgeDetector::parameters.

Member Function Documentation

virtual functor::parameters* lti::colorEdgesGS::parameters::clone ( ) const [virtual]

returns a pointer to a clone of the parameters

Reimplemented from lti::edgeDetector::parameters.

parameters& lti::colorEdgesGS::parameters::copy ( const parameters & other )

copy the contents of a parameters object

Parameters:

other

the parameters object to be copied

Returns:: a reference to this parameters object

Reimplemented from lti::edgeDetector::parameters.

const char* lti::colorEdgesGS::parameters::getTypeName ( ) const [virtual]

returns name of this type

Reimplemented from lti::edgeDetector::parameters.

bool lti::colorEdgesGS::parameters::measureNoise	(	const image &	img,
		const rectangle &	window = `rectangle(0, 0, std::numeric_limits< int >::max(), std::numeric_limits< int >::max())`
	)

Assuming the given image corresponds to a homogeneous color patch, the noise standard deviation will be computed as the standard deviation for each channel.

The result will be left in the attribute noiseStdDeviation.

Parameters:

	img	image containing a homogeneous color patch.
	window	region of the image to be considered.

Returns:: true if successful, false otherwise.

parameters& lti::colorEdgesGS::parameters::operator= ( const parameters & other )

copy the contents of a parameters object

Parameters:

other

the parameters object to be copied

Returns:: a reference to this parameters object

Reimplemented from lti::edgeDetector::parameters.

virtual bool lti::colorEdgesGS::parameters::read	(	ioHandler &	handler,
		const bool	complete = `true`
	)			`[virtual]`

read the parameters from the given ioHandler

Parameters:

	handler	the ioHandler to be used
	complete	if true (the default) the enclosing begin/end will be also written, otherwise only the data block will be written.

Returns:: true if write was successful

Reimplemented from lti::edgeDetector::parameters.

virtual bool lti::colorEdgesGS::parameters::write	(	ioHandler &	handler,
		const bool	complete = `true`
	)			const `[virtual]`

write the parameters in the given ioHandler

Parameters:

	handler	the ioHandler to be used
	complete	if true (the default) the enclosing begin/end will be also written, otherwise only the data block will be written.

Returns:: true if write was successful

Reimplemented from lti::edgeDetector::parameters.

Member Data Documentation

gradientFunctor::parameters lti::colorEdgesGS::parameters::gradient

Parameters for the gradient functor used to compute single channel gradients.

The parameters used are mostly the default ones, but the mode is always set to cartesian, since that is the mode required by this functor, and the default kernel is the Sobel.

ubyte lti::colorEdgesGS::parameters::highlightEdgeValue

Value used to mark the highlight edges.

Default value 192

trgbPixel<float> lti::colorEdgesGS::parameters::noiseStdDeviation

The algorithm of Gevers and Stokman requires the standard deviation for the noise at each channel.

You can compute this standard deviation with the methods of this parameter class measureNoise().

The noise standard deviation is computed for the range [0,255].

Default value: trgbPixel<float>(1.5f,1.5f,1.5f)

ubyte lti::colorEdgesGS::parameters::shadowEdgeValue

Value used to mark the shadow edges.

Default value 128

float lti::colorEdgesGS::parameters::uncertaintyFactor