Functions
bool	CreateMCFromImageList (SIL ImageList, const char MantoControlWord, TMantoNotify Notify, void NotifyData, TDecisionBoundary Boundary, MCF &MC)
	This is the principal learning function, which creates a MCF object from the specified Sample Image List using the specified preprocessing code. More...

TDecisionBoundary	GetMCBoundaryType (MCF MC)
	This function returns the permeability of the decision surface. More...

const char *	GetMCComment (MCF MC)
	This function returns a pointer to the comment field within the MCF object. More...

const char *	GetMCControlword (MCF MC)
	This function returns the preprocessing code which was used for generation of the MCF object. More...

void	GetMCDimensions (MCF MC, cvbdim_t &Width, cvbdim_t &Height, cvbdim_t &X, cvbdim_t &Y, cvbdim_t &Dimension)
	This function returns the image format and origin position of the MCF object. More...

const char *	GetMCExcludedClass (MCF MC)
	If a class is excluded from pattern matching, this function returns its ID or an empty string otherwise. More...

double	GetMCLearnResult (MCF MC)
	This function returns a characteristic number describing approximately the classifiers capability to separate the feature space during learning. More...

int	GetMCNumClasses (MCF MC)
	This function returns the number of classes contained in the MCF object. More...

bool	LoadMC (const char *Filename, MCF &MC)
	This function creates a MCF object by loading it from disk. More...

bool	MantoColourTransform (IMG Image, IMG &ImgOut)
	This function creates a nine-planar colour image from a three-planar colour image by adding colour planes containing the information of RR, RG, RB, GG, GB, BB in plane 4 to 9 (normalised to a dynamic range of 0...255). More...

bool	MCAppendResults (SEARCHRESULTS &Results1, SEARCHRESULTS Results2)
	This function appends the items of Results2 onto the end of Results1. More...

cvbval_t	MCClassIDToClassIndex (MCF MC, const char *ClassID)
	This function returns the class label for the specified class index. More...

const char *	MCClassIndexToClassID (OBJ MC, cvbval_t ClassIndex)
	This function returns the index of the specified class in the MCF. More...

bool	MCReadToken (MCF MC, IMG AImage, long Left, long Top, long Right, long Bottom, bool Vote, bool PointSensity, long MaxCount, double Threshold, long ASearchID, long Xadvance, long YAdvance, long Radius, SEARCHRESULTS &String)
	This function scans the frame (Left, Top, Right, Bottom) of the image AImage to generate a list (results) of pattern matches. More...

bool	MCReleaseResults (SEARCHRESULTS Results)
	This function frees the memory resources associated with a list of search results. More...

bool	MCRetractSearchResult (SEARCHRESULTS Results, long Index)
	This function removes an individual search result from the list. More...

bool	MCSearch (MCF MC, IMG AImage, cvbdim_t Left, cvbdim_t Top, cvbdim_t Right, cvbdim_t Bottom, bool Vote, bool DotSensitivity, bool CreateResultImage, double &XPos, double &YPos, double &Quality, char *ClassID, IMG &ResultImage)
	This function scans the frame (Left, Top, Right, Bottom) of the image AImage for best pattern match. More...

bool	MCSearchAll (MCF MC, IMG AImage, cvbdim_t Left, cvbdim_t Top, cvbdim_t Right, cvbdim_t Bottom, bool Vote, bool DotSensitivity, long MaxCount, double Threshold, long ASearchID, SEARCHRESULTS &Results)
	This function scans the frame (Left, Top, Right, Bottom) of the image AImage to generate a list (Results) of pattern matches. More...

bool	MCSearchAllEx (MCF MC, IMG AImage, cvbdim_t Left, cvbdim_t Top, cvbdim_t Right, cvbdim_t Bottom, bool Vote, bool DotSensitivity, long MaxCount, double Threshold, long ASearchID, long Granularity, SEARCHRESULTS &Results)
	This function scans the frame (Left, Top, Right, Bottom) of the image AImage to generate a list (Results) of pattern matches. More...

PSRESULT	MCSearchResult (SEARCHRESULTS Results, long Index)
	This function returns a pointer to a record to access the data corresponding to an individual search result. More...

bool	MCSearchResultRef (SEARCHRESULTS Results, long Index, PSRESULT Result)
	This function returns a pointer to a record to access the data corresponding to an individual search result from a SEARCHRESULTS result list. More...

long	MCSearchResultsCount (SEARCHRESULTS Results)
	This function returns the number of records in the specified list. More...

bool	MCSeparateResults (SEARCHRESULTS Results, long Separation)
	This function thins out the list by a given separation parameter. More...

bool	MCSortResultsByConfidence (SEARCHRESULTS Results)
	This function sorts the list of results by decreasing confidence, so that the best results come first in the list. More...

bool	MCSortResultsByPosition (SEARCHRESULTS Results, double X, double Y)
	This function sorts the list in the direction specified by the vector (X,Y). More...

bool	MCTestCLFWithImageList (MCF MC, SIL TestList, bool Vote, double &ErrorRate)
	This function probes the classification capabilities of a MCF object by means of a SIL TestList containing appropriate test samples. More...

bool	MCTruncateResults (SEARCHRESULTS Results, long N)
	This function retains the first N items in the list, deleting the rest. More...

void	ReleaseMC (MCF MC)
	This function decrements the internal reference counter of the MCF object by one. More...

void	SetMCComment (MCF MC, const char *Comment)
	This function specifies an arbitrary comment for the MCF object. More...

void	SetMCExcludedClass (MCF MC, const char *ClassID)
	This function specifies the excluded class during subsequent calls of MCSearch. More...

void	ShareMC (MCF MC)
	This function increments the internal reference counter of the MCF object by one. More...

bool	StoreMC (const char *Filename, MCF MC)
	This function writes the MCF object to disk. More...

Detailed Description

Function Documentation

◆ CreateMCFromImageList()

bool CreateMCFromImageList	(	SIL	ImageList,
		const char *	MantoControlWord,
		TMantoNotify	Notify,
		void *	NotifyData,
		TDecisionBoundary	Boundary,
		MCF &	MC
	)

This is the principal learning function, which creates a MCF object from the specified Sample Image List using the specified preprocessing code.

If the callback function Notify is nonzero, it is executed regularly, gives information about execution progress and enables execution interruption. For more information and the definition see TMantoNotify function.

Parameters

[in]	ImageList	Pointer to a Sample Image List (SIL) object.
[in]	MantoControlWord	Preprocessing code for multi resolution filter.
[in]	Notify	Callback function as described in the TMantoNotify function.
[in]	NotifyData	Pointer to a window which handles the callback function calls.
[in]	Boundary	This is an enumerated type to control the permeability of the decision surface. See TDecisionBoundary for a detailed description. See section Binary Classifiers, Decision Surfaces and Pattern Quality for an explanation. When in doubt pick TDB_Soft.
[out]	MC	Pointer to the newly created MCF object.

Returns: TRUE if generated MCF object is given in the parameter MC, FALSE otherwise.

Supported platforms:: Win32

◆ GetMCBoundaryType()

TDecisionBoundary GetMCBoundaryType ( MCF MC )

This function returns the permeability of the decision surface.

Parameters

[in] MC Pointer to a MCF object.

Returns: Indicates the current permeability of the decision surface.

Supported platforms:: Win32

◆ GetMCComment()

const char * GetMCComment ( MCF MC )

This function returns a pointer to the comment field within the MCF object.

Parameters

[in] MC Pointer to a MCF object.

Returns: Comment field within the MCF object.

Supported platforms:: Win32

◆ GetMCControlword()

const char * GetMCControlword ( MCF MC )

This function returns the preprocessing code which was used for generation of the MCF object.

Parameters

[in] MC Pointer to a MCF object.

Returns: Preprocessing code.

Supported platforms:: Win32

◆ GetMCDimensions()

void GetMCDimensions	(	MCF	MC,
		cvbdim_t &	Width,
		cvbdim_t &	Height,
		cvbdim_t &	X,
		cvbdim_t &	Y,
		cvbdim_t &	Dimension
	)

This function returns the image format and origin position of the MCF object.

Parameters

[in]	MC	Pointer to a MCF object.
[out]	Width	Width of feature window.
[out]	Height	Height of feature window.
[out]	X	X-position of sample origin.
[out]	Y	Y-position of sample origin.
[out]	Dimension	Number of colour planes.

Supported platforms:: Win32

◆ GetMCExcludedClass()

const char * GetMCExcludedClass ( MCF MC )

If a class is excluded from pattern matching, this function returns its ID or an empty string otherwise.

Parameters

[in] MC Pointer to a MCF object.

Returns: ID of excluded class or an empty string otherwise.

Supported platforms:: Win32

◆ GetMCLearnResult()

double GetMCLearnResult ( MCF MC )

This function returns a characteristic number describing approximately the classifiers capability to separate the feature space during learning.

Attention: If this number is less than or equal to zero, the classifier is useless for classification.

Parameters

[in] MC Pointer to a MCF object.

Returns: Characteristic number describing approximately the classifiers capability to separate the feature space.

Supported platforms:: Win32

◆ GetMCNumClasses()

int GetMCNumClasses ( MCF MC )

This function returns the number of classes contained in the MCF object.

Parameters

[in] MC Pointer to a MCF object.

Returns: Number of classes.

Supported platforms:: Win32

◆ LoadMC()

bool LoadMC	(	const char *	Filename,
		MCF &	MC
	)

This function creates a MCF object by loading it from disk.

Parameters

[in]	Filename	Name of MCF file.
[out]	MC	Pointer to the MCF object.

Returns: TRUE on success, FALSE otherwise.

Supported platforms:: Win32

◆ MantoColourTransform()

bool MantoColourTransform	(	IMG	Image,
		IMG &	ImgOut
	)

This function creates a nine-planar colour image from a three-planar colour image by adding colour planes containing the information of R*R, R*G, R*B, G*G, G*B, B*B in plane 4 to 9 (normalised to a dynamic range of 0...255).

Parameters

[in]	Image	Handle to the source image used for the transformation.
[out]	ImgOut	Handle to the output image that will receive the newly created result image.

Returns: TRUE on success, FALSE otherwise.

Supported platforms:: Win32

◆ MCAppendResults()

bool MCAppendResults	(	SEARCHRESULTS &	Results1,
		SEARCHRESULTS	Results2
	)

This function appends the items of Results2 onto the end of Results1.

If Results1 is initialised to a Nil pointer, a copy of Results2 is created. 
The \a SearchID parameter in #MCSearchAll and in the individual item records lets you keep 
track from which call to #MCSearchAll a given record originates.

Parameters

[in,out]	Results1	Pointer to the list of search results to which Results2 is to be appended.
[in]	Results2	Pointer to a list of search results.

Returns: TRUE on success, FALSE if the calling parameters contain illegal data.

Supported platforms:: Win32

◆ MCClassIDToClassIndex()

cvbval_t MCClassIDToClassIndex	(	MCF	MC,
		const char *	ClassID
	)

This function returns the class label for the specified class index.

Attention: Note that class indices start at zero.

Parameters

[in]	MC	Pointer to the MCF object.
[in]	ClassID	Index of class.

Returns: Class label of specified class index.

Supported platforms:: Win32

◆ MCClassIndexToClassID()

const char * MCClassIndexToClassID	(	OBJ	MC,
		cvbval_t	ClassIndex
	)

This function returns the index of the specified class in the MCF.

Attention: Note that class indices start at zero. Also please note that you should neither allocate nor de-allocates the memory for the string, but just keep in mind that the returned class id is only valid as long as you hold the corresponding classifier in memory.

Parameters

[in]	MC	Pointer to the MCF object.
[in]	ClassIndex	Index of class.

Returns: Index of specified class.

Supported platforms:: Win32

◆ MCReadToken()

bool MCReadToken	(	MCF	MC,
		IMG	AImage,
		long	Left,
		long	Top,
		long	Right,
		long	Bottom,
		bool	Vote,
		bool	PointSensity,
		long	MaxCount,
		double	Threshold,
		long	ASearchID,
		long	Xadvance,
		long	YAdvance,
		long	Radius,
		SEARCHRESULTS &	String
	)

This function scans the frame (Left, Top, Right, Bottom) of the image AImage to generate a list (results) of pattern matches.

After the first found pattern, the search window will be moved by Xadvance and YAdvance and the resulting window is again searched for a result and so on. The result is a list of results in the form of a SEARCHRESULTS structure as commonly used in Manto (see also MCSearchAll, MCSearchAllEx).

Parameters

[in]	MC	Pointer to the MCF object.
[in]	AImage	Handle to the source image to scan.
[in]	Left	Left coordinate of the search area.
[in]	Top	Top coordinate of the search area.
[in]	Right	Right coordinate of the search area.
[in]	Bottom	Bottom coordinate of the search area.
[in]	Vote	Use voting mechanism for classification quality (see section Multiclass Classifiers, Vote and Multiclass Performance).
[in]	PointSensity	Switch for sensitivity on dot-signs in class labels.
[in]	MaxCount	Maximal number of results to be returned. To really get all the instances that are present, however, you should set this value significantly higher than the number of instances you expect to be present.
[in]	Threshold	A threshold for the minimal confidence quality, for which a match is entered into the list of results.
[in]	ASearchID	Search operation within the results list (see MCAppendResults).
[in]	Xadvance	X-component of the advance vector.
[in]	YAdvance	Y-component of the advance vector.
[in]	Radius	Relative expectation window (as circle) for the next pattern.
[out]	String	Result list for further treatment (e.g., with MCSearchResultsCount, MCSearchResultRef).

Returns: TRUE on success, FALSE otherwise.

Supported platforms:: Win32

◆ MCReleaseResults()

bool MCReleaseResults ( SEARCHRESULTS Results )

This function frees the memory resources associated with a list of search results.

Parameters

[in] Results A pointer to a list of search results as created by the function MCSearchAll.

Returns: TRUE on success, FALSE if the calling parameters contain illegal data.

Supported platforms:: Win32

◆ MCRetractSearchResult()

bool MCRetractSearchResult	(	SEARCHRESULTS	Results,
		long	Index
	)

This function removes an individual search result from the list.

Parameters

[in]	Results	A pointer to a list of search as created by the function MCSearchAll.
[in]	Index	Zero-based position of the record to be removed.

Returns: TRUE on success, FALSE if the calling parameters contain illegal data.

Supported platforms:: Win32

◆ MCSearch()

bool MCSearch	(	MCF	MC,
		IMG	AImage,
		cvbdim_t	Left,
		cvbdim_t	Top,
		cvbdim_t	Right,
		cvbdim_t	Bottom,
		bool	Vote,
		bool	DotSensitivity,
		bool	CreateResultImage,
		double &	XPos,
		double &	YPos,
		double &	Quality,
		char *	ClassID,
		IMG &	ResultImage
	)

This function scans the frame (Left, Top, Right, Bottom) of the image AImage for best pattern match.

If the return value is TRUE, the values of XPos and YPos give the position of the best match, Model is the corresponding class label and Quality is the classification quality. If no pattern was found, ClassID is an empty string and Quality equals zero.

For purposes of post processing the creation of a ResultImage can be requested by setting CreateResultImage to TRUE. Note that a requested ResultImage should be released after use! For a more detailed description of the ResultImage see section The Search Function.

The parameter DotSensitivity controls the format of the returned ClassID name by building equivalent class names for class labels differing only after the control character "." (dot). If DotSensitive is activated and the best match pattern label is part of such a set of equivalent class names, ClassID will merely contain the first part of the class name i.e., the characters up to the dot sign. If DotSensitivity is FALSE, the dot in a class name does not have a special meaning. Note that the excluded-class property of the classifier plays an important role during searching, since it can be used to condemn a class to inactivity during pattern match. For a thorough description of this important possibility see section Searching and Excluded Classes.

Parameters

[in]	MC	Pointer to the MCF object.
[in]	AImage	Handle to the source image to be scanned.
[in]	Left	Left coordinate of the search area.
[in]	Top	Top coordinate of the search area.
[in]	Right	Right coordinate of the search area.
[in]	Bottom	Bottom coordinate of the search area.
[in]	Vote	Use voting mechanism for classification quality (see section Multiclass classifiers, vote and multiclass performance).
[in]	DotSensitivity	Switch for sensitivity on dot-signs in class labels (see section Searching and Excluded Classes).
[in]	CreateResultImage	Controls whether the ResultImage is created or not.
[out]	XPos	X-coordinate of best match pattern.
[out]	YPos	Y-coordinate of best match pattern.
[out]	Quality	Classification quality for best match pattern.
[out]	ClassID	Class label of best match pattern.
[out]	ResultImage	Handle to the result image which can be used for post processing.

Returns: TRUE on success, FALSE if either the colour dimension of AImage is not compatible to the MCF object or the search frame cannot hold any possible origins of a feature window without exceeding the image dimensions.

Supported platforms:: Win32

◆ MCSearchAll()

bool MCSearchAll	(	MCF	MC,
		IMG	AImage,
		cvbdim_t	Left,
		cvbdim_t	Top,
		cvbdim_t	Right,
		cvbdim_t	Bottom,
		bool	Vote,
		bool	DotSensitivity,
		long	MaxCount,
		double	Threshold,
		long	ASearchID,
		SEARCHRESULTS &	Results
	)

This function scans the frame (Left, Top, Right, Bottom) of the image AImage to generate a list (Results) of pattern matches.

If the return value is TRUE, the value of Results points to a corresponding list. Each entry of the list describes a corresponding match as explained in the description of MCSearchResult. The list can be manipulated by the functions MCReleaseResults, MCSearchResult, MCRetractSearchResult, MCSortResultsByConfidence, MCSortResultsByPosition, MCTruncateResults and MCAppendResults.

The parameter DotSensitivity functions as in MCSearch.

Parameters

[in]	MC	Pointer to a MCF object.
[in]	AImage	Handle to source image to be scanned.
[in]	Left	Left coordinate of the search area.
[in]	Top	Top coordinate of the search area.
[in]	Right	Right coordinate of the search area.
[in]	Bottom	Bottom coordinate of the search area.
[in]	Vote	Use voting mechanism for classification quality (see section Multiclass Classifiers, Vote and Multiclass Performance).
[in]	DotSensitivity	Switch for sensitivity on dot-signs in class labels.
[in]	MaxCount	Maximal number of results to be returned. To really get all the instances that are present, however, you should set this value significantly higher than the number of instances you expect to be present.
[in]	Threshold	A threshold for the minimal confidence quality, for which a match is entered into the list of results.
[in]	ASearchID	ID to identify the search operation within the results list (see MCAppendResults).
[out]	Results	Pointer to the list of results. The memory resources associated with this list must eventually be freed with a call to MCReleaseResults. See SEARCHRESULTS for further description.

Returns: TRUE on success, FALSE if either the colour dimension of AImage is not compatible to the MCF object or the search frame cannot hold any possible origins of a feature window without exceeding the image dimensions.

Supported platforms:: Win32

◆ MCSearchAllEx()

bool MCSearchAllEx	(	MCF	MC,
		IMG	AImage,
		cvbdim_t	Left,
		cvbdim_t	Top,
		cvbdim_t	Right,
		cvbdim_t	Bottom,
		bool	Vote,
		bool	DotSensitivity,
		long	MaxCount,
		double	Threshold,
		long	ASearchID,
		long	Granularity,
		SEARCHRESULTS &	Results
	)

This function scans the frame (Left, Top, Right, Bottom) of the image AImage to generate a list (Results) of pattern matches.

If the return value is TRUE, the value of Results points to a corresponding list. Each entry of the list describes a corresponding match as explained in the description of MCSearchResult. The list can be manipulated by the functions MCReleaseResults, MCSearchResult, MCRetractSearchResult, MCSortResultsByConfidence, MCSortResultsByPosition, MCTruncateResults and MCAppendResults.

The parameter DotSensitivity functions as in MCSearch.

Parameters

[in]	MC	Pointer to a MCF object.
[in]	AImage	Handle to source image to be scanned.
[in]	Left	Left coordinate of the search area.
[in]	Top	Top coordinate of the search area.
[in]	Right	Right coordinate of the search area.
[in]	Bottom	Bottom coordinate of the search area.
[in]	Vote	Use voting mechanism for classification quality (see section Multiclass Classifiers, Vote and Multiclass Performance).
[in]	DotSensitivity	Switch for sensitivity on dot-signs in class labels.
[in]	MaxCount	Maximal number of results to be returned. To really get all the instances that are present, however, you should set this value significantly higher than the number of instances you expect to be present.
[in]	Threshold	A threshold for the minimal confidence quality, for which a match is entered into the list of results.
[in]	ASearchID	ID to identify the search operation within the results list (see MCAppendResults).
[in]	Granularity	Granularity with which the image will be searched. Every (2^Granularity)th pixel will be classified. The default is Granularity = Length of Preprocessing Code (this setting is used by MCSearchAll). Attention: Lowering Granularity will drastically increase processing time!
[out]	Results	Pointer to the list of results. The memory resources associated with this list must eventually be freed with a call to MCReleaseResults. See SEARCHRESULTS for further description.

Returns: TRUE on success, FALSE if either the colour dimension of AImage is not compatible to the MCF object or the search frame cannot hold any possible origins of a feature window without exceeding the image dimensions.

Supported platforms:: Win32

◆ MCSearchResult()

PSRESULT MCSearchResult	(	SEARCHRESULTS	Results,
		long	Index
	)

This function returns a pointer to a record to access the data corresponding to an individual search result.

\a Results specifies the list, \a Index the zero based position within the list.

Parameters

[in]	Results	A pointer to a list of search results as created by the function MCSearchAll.
[in]	Index	Zero-based position of the record.

Returns: The record structure is defined in PSRESULT.

Supported platforms:: Win32

◆ MCSearchResultRef()

bool MCSearchResultRef	(	SEARCHRESULTS	Results,
		long	Index,
		PSRESULT	Result
	)

This function returns a pointer to a record to access the data corresponding to an individual search result from a SEARCHRESULTS result list.

Results specifies the list, Index the zero based position within the list.

Parameters

[in]	Results	A pointer to a list of search results as created by the function MCSearchAll.
[in]	Index	Zero-based position of the record.
[out]	Result	Extracted result as defined in PSRESULT.

Returns: TRUE on success, FALSE if the calling parameters contain illegal data.

Supported platforms:: Win32

◆ MCSearchResultsCount()

long MCSearchResultsCount ( SEARCHRESULTS Results )

This function returns the number of records in the specified list.

Parameters

[in] Results A pointer to a list of search as created by the function MCSearchAll.

Returns: Number of records in the specified list.

Supported platforms:: Win32

◆ MCSeparateResults()

bool MCSeparateResults	(	SEARCHRESULTS	Results,
		long	Separation
	)

This function thins out the list by a given separation parameter.

This function first sorts the list by decreasing confidence. 
Then it considers all items, starting with the best, and deletes all those entries from the rest 
of the list, whose coordinates differ from the given item by less than the Separation parameter. 
The effect is to thin out the list, retaining the best items in each square of side length 
2*\a Separation.

Attention: Note that, if you also want to sort your results using e.g., MCSortResultsByPosition, you must call MCSeparateResults before you sort your results!

Parameters

[in,out]	Results	A pointer to a list of search as created by the function MCSearchAll.
[in]	Separation	Spatial separation (in pixels) of the items of the resulting list.

Returns: TRUE on success, if the calling parameters contain illegal data.

Supported platforms:: Win32

◆ MCSortResultsByConfidence()

bool MCSortResultsByConfidence ( SEARCHRESULTS Results )

This function sorts the list of results by decreasing confidence, so that the best results come first in the list.

Parameters

[in] Results A pointer to a list of search as created by the function MCSearchAll.

Returns: TRUE on success, if the calling parameters contain illegal data.

Supported platforms:: Win32

◆ MCSortResultsByPosition()

bool MCSortResultsByPosition	(	SEARCHRESULTS	Results,
		double	X,
		double	Y
	)

This function sorts the list in the direction specified by the vector (X,Y).

Parameters

[in]	Results	A pointer to a list of search as created by the function MCSearchAll.
[in]	X	X-direction of the vector whose argument gives the sorting direction. The modulus is ignored.
[in]	Y	Y-direction of the vector whose argument gives the sorting direction. The modulus is ignored.

Returns: TRUE on success, if the calling parameters contain illegal data.

Supported platforms:: Win32

◆ MCTestCLFWithImageList()

bool MCTestCLFWithImageList	(	MCF	MC,
		SIL	TestList,
		bool	Vote,
		double &	ErrorRate
	)

This function probes the classification capabilities of a MCF object by means of a SIL TestList containing appropriate test samples.

Attention: Note that the sample instance generation mechanism of the test SIL is used. Vote specifies if the voting mechanism is used for classification. ErrorRate gives the rate of misclassification in percent (i.e., 100 times number of mis-classifications over total number of generated samples).

Parameters

[in]	MC	Pointer to the MCF object.
[in]	TestList	Pointer to the SIL object containing test samples.
[in]	Vote	Specifies the voting mechanism for classification quality.
[out]	ErrorRate	Determined rate of misclassification in percent.

Returns: TRUE on success, FALSE if the MC and TestList are not compatible that means that either feature window dimensions or sample origins or colour resolutions differ.

Supported platforms:: Win32

◆ MCTruncateResults()

bool MCTruncateResults	(	SEARCHRESULTS	Results,
		long	N
	)

This function retains the first N items in the list, deleting the rest.

Parameters

[in,out]	Results	A pointer to a list of search as created by the function MCSearchAll.
[in]	N	Number of leading items to be kept.

Returns: TRUE on success, if the calling parameters contain illegal data.

Supported platforms:: Win32

◆ ReleaseMC()

void ReleaseMC ( MCF MC )

This function decrements the internal reference counter of the MCF object by one.

If the reference counter drops to zero, the \a MCF object is destroyed.

Parameters

[in] MC Pointer to the MCF object.

Supported platforms:: Win32

◆ SetMCComment()

void SetMCComment	(	MCF	MC,
		const char *	Comment
	)

This function specifies an arbitrary comment for the MCF object.

Parameters

[in]	MC	Pointer to a MCF object.
[in]	Comment	Pointer to the comment text.

Supported platforms:: Win32

◆ SetMCExcludedClass()

void SetMCExcludedClass	(	MCF	MC,
		const char *	ClassID
	)

This function specifies the excluded class during subsequent calls of MCSearch.

Specify an empty string for \a ClassID if no class should be excluded (default).
See section <i>Searching and Excluded Classes</i> for further details.

Parameters

[in]	MC	Pointer to a MCF object.
[in]	ClassID	ID of excluded class or empty string.

Supported platforms:: Win32

◆ ShareMC()

void ShareMC ( MCF MC )

This function increments the internal reference counter of the MCF object by one.

Parameters

[in] MC Pointer to the MCF object.

Supported platforms:: Win32

◆ StoreMC()

bool StoreMC	(	const char *	Filename,
		MCF	MC
	)

This function writes the MCF object to disk.

Parameters

[in]	Filename	Name of MCF file.
[in]	MC	Pointer to the MCF object.

Returns: TRUE on success, FALSE otherwise.

Supported platforms:: Win32

Functions

Detailed Description

Function Documentation

◆ CreateMCFromImageList()

◆ GetMCBoundaryType()

◆ GetMCComment()

◆ GetMCControlword()

◆ GetMCDimensions()

◆ GetMCExcludedClass()

◆ GetMCLearnResult()

◆ GetMCNumClasses()

◆ LoadMC()

◆ MantoColourTransform()

◆ MCAppendResults()

◆ MCClassIDToClassIndex()

◆ MCClassIndexToClassID()

◆ MCReadToken()

◆ MCReleaseResults()

◆ MCRetractSearchResult()

◆ MCSearch()

◆ MCSearchAll()

◆ MCSearchAllEx()

◆ MCSearchResult()

◆ MCSearchResultRef()

◆ MCSearchResultsCount()

◆ MCSeparateResults()

◆ MCSortResultsByConfidence()

◆ MCSortResultsByPosition()

◆ MCTestCLFWithImageList()

◆ MCTruncateResults()

◆ ReleaseMC()

◆ SetMCComment()

◆ SetMCExcludedClass()

◆ ShareMC()

◆ StoreMC()