Manto (Manto.dll) 15.0
MCF-Functions

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 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). 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]ImageListPointer to a Sample Image List (SIL) object.
[in]MantoControlWordPreprocessing code for multi resolution filter.
[in]NotifyCallback function as described in the TMantoNotify function.
[in]NotifyDataPointer to a window which handles the callback function calls.
[in]BoundaryThis 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]MCPointer 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]MCPointer 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]MCPointer 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]MCPointer 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]MCPointer to a MCF object.
[out]WidthWidth of feature window.
[out]HeightHeight of feature window.
[out]XX-position of sample origin.
[out]YY-position of sample origin.
[out]DimensionNumber 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]MCPointer 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]MCPointer 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]MCPointer 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]FilenameName of MCF file.
[out]MCPointer 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]ImageHandle to the source image used for the transformation.
[out]ImgOutHandle 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]Results1Pointer to the list of search results to which Results2 is to be appended.
[in]Results2Pointer 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]MCPointer to the MCF object.
[in]ClassIDIndex 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]MCPointer to the MCF object.
[in]ClassIndexIndex 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]MCPointer to the MCF object.
[in]AImageHandle to the source image to scan.
[in]LeftLeft coordinate of the search area.
[in]TopTop coordinate of the search area.
[in]RightRight coordinate of the search area.
[in]BottomBottom coordinate of the search area.
[in]VoteUse voting mechanism for classification quality (see section Multiclass Classifiers, Vote and Multiclass Performance).
[in]PointSensitySwitch for sensitivity on dot-signs in class labels.
[in]MaxCountMaximal 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]ThresholdA threshold for the minimal confidence quality, for which a match is entered into the list of results.
[in]ASearchIDSearch operation within the results list (see MCAppendResults).
[in]XadvanceX-component of the advance vector.
[in]YAdvanceY-component of the advance vector.
[in]RadiusRelative expectation window (as circle) for the next pattern.
[out]StringResult 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]ResultsA 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]ResultsA pointer to a list of search as created by the function MCSearchAll.
[in]IndexZero-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]MCPointer to the MCF object.
[in]AImageHandle to the source image to be scanned.
[in]LeftLeft coordinate of the search area.
[in]TopTop coordinate of the search area.
[in]RightRight coordinate of the search area.
[in]BottomBottom coordinate of the search area.
[in]VoteUse voting mechanism for classification quality (see section Multiclass classifiers, vote and multiclass performance).
[in]DotSensitivitySwitch for sensitivity on dot-signs in class labels (see section Searching and Excluded Classes).
[in]CreateResultImageControls whether the ResultImage is created or not.
[out]XPosX-coordinate of best match pattern.
[out]YPosY-coordinate of best match pattern.
[out]QualityClassification quality for best match pattern.
[out]ClassIDClass label of best match pattern.
[out]ResultImageHandle 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]MCPointer to a MCF object.
[in]AImageHandle to source image to be scanned.
[in]LeftLeft coordinate of the search area.
[in]TopTop coordinate of the search area.
[in]RightRight coordinate of the search area.
[in]BottomBottom coordinate of the search area.
[in]VoteUse voting mechanism for classification quality (see section Multiclass Classifiers, Vote and Multiclass Performance).
[in]DotSensitivitySwitch for sensitivity on dot-signs in class labels.
[in]MaxCountMaximal 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]ThresholdA threshold for the minimal confidence quality, for which a match is entered into the list of results.
[in]ASearchIDID to identify the search operation within the results list (see MCAppendResults).
[out]ResultsPointer 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]MCPointer to a MCF object.
[in]AImageHandle to source image to be scanned.
[in]LeftLeft coordinate of the search area.
[in]TopTop coordinate of the search area.
[in]RightRight coordinate of the search area.
[in]BottomBottom coordinate of the search area.
[in]VoteUse voting mechanism for classification quality (see section Multiclass Classifiers, Vote and Multiclass Performance).
[in]DotSensitivitySwitch for sensitivity on dot-signs in class labels.
[in]MaxCountMaximal 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]ThresholdA threshold for the minimal confidence quality, for which a match is entered into the list of results.
[in]ASearchIDID to identify the search operation within the results list (see MCAppendResults).
[in]GranularityGranularity 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]ResultsPointer 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]ResultsA pointer to a list of search results as created by the function MCSearchAll.
[in]IndexZero-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]ResultsA pointer to a list of search results as created by the function MCSearchAll.
[in]IndexZero-based position of the record.
[out]ResultExtracted 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]ResultsA 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]ResultsA pointer to a list of search as created by the function MCSearchAll.
[in]SeparationSpatial 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]ResultsA 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]ResultsA pointer to a list of search as created by the function MCSearchAll.
[in]XX-direction of the vector whose argument gives the sorting direction. The modulus is ignored.
[in]YY-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]MCPointer to the MCF object.
[in]TestListPointer to the SIL object containing test samples.
[in]VoteSpecifies the voting mechanism for classification quality.
[out]ErrorRateDetermined 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]ResultsA pointer to a list of search as created by the function MCSearchAll.
[in]NNumber 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]MCPointer 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]MCPointer to a MCF object.
[in]CommentPointer 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]MCPointer to a MCF object.
[in]ClassIDID 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]MCPointer 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]FilenameName of MCF file.
[in]MCPointer to the MCF object.
Returns
TRUE on success, FALSE otherwise.
Supported platforms:
Win32