FEATURE_SET Classify::ExtractPicoFeatures(TBLOB *Blob) {
/*
** Parameters:
** Blob blob to extract pico-features from
** LineStats statistics on text row blob is in
** Globals:
** classify_norm_method normalization method currently specified
** Operation: Dummy for now.
** Return: Pico-features for Blob.
** Exceptions: none
** History: 9/4/90, DSJ, Created.
*/
LIST Outlines;
LIST RemainingOutlines;
MFOUTLINE Outline;
FEATURE_SET FeatureSet;
FLOAT32 XScale, YScale;
FeatureSet = NewFeatureSet(MAX_PICO_FEATURES);
Outlines = ConvertBlob(Blob);
NormalizeOutlines(Outlines, &XScale, &YScale);
RemainingOutlines = Outlines;
iterate(RemainingOutlines) {
Outline = (MFOUTLINE) first_node (RemainingOutlines);
ConvertToPicoFeatures2(Outline, FeatureSet);
}
if (classify_norm_method == baseline)
NormalizePicoX(FeatureSet);
FreeOutlines(Outlines);
return (FeatureSet);
} /* ExtractPicoFeatures */
/*---------------------------------------------------------------------------*/
CHAR_FEATURES BlobMicroFeatures(TBLOB *Blob, const DENORM& denorm) {
/*
** Parameters:
** Blob blob to extract micro-features from
** denorm control parameter to feature extractor
** Operation:
** This routine extracts micro-features from the specified
** blob and returns a list of the micro-features. All
** micro-features are normalized according to the specified
** line statistics.
** Return: List of micro-features extracted from the blob.
** Exceptions: none
** History: 7/21/89, DSJ, Created.
*/
MICROFEATURES MicroFeatures = NIL_LIST;
FLOAT32 XScale, YScale;
LIST Outlines;
LIST RemainingOutlines;
MFOUTLINE Outline;
INT_FEATURE_ARRAY blfeatures;
INT_FEATURE_ARRAY cnfeatures;
INT_FX_RESULT_STRUCT results;
if (Blob != NULL) {
Outlines = ConvertBlob (Blob);
if (!ExtractIntFeat(Blob, denorm, blfeatures, cnfeatures, &results))
return NULL;
XScale = 0.2f / results.Ry;
YScale = 0.2f / results.Rx;
RemainingOutlines = Outlines;
iterate(RemainingOutlines) {
Outline = (MFOUTLINE) first_node (RemainingOutlines);
CharNormalizeOutline (Outline,
results.Xmean, results.Ymean,
XScale, YScale);
}
RemainingOutlines = Outlines;
iterate(RemainingOutlines) {
Outline = (MFOUTLINE) first_node (RemainingOutlines);
FindDirectionChanges(Outline, classify_min_slope, classify_max_slope);
MarkDirectionChanges(Outline);
SmearExtremities(Outline, XScale, YScale);
MicroFeatures = ConvertToMicroFeatures (Outline, MicroFeatures);
}
FreeOutlines(Outlines);
}
/**
* Operation: Dummy for now.
*
* Globals:
* - classify_norm_method normalization method currently specified
* @param Blob blob to extract pico-features from
* @return Pico-features for Blob.
* @note Exceptions: none
* @note History: 9/4/90, DSJ, Created.
*/
FEATURE_SET Classify::ExtractPicoFeatures(TBLOB * Blob) {
LIST Outlines;
LIST RemainingOutlines;
MFOUTLINE Outline;
FEATURE_SET FeatureSet;
FLOAT32 XScale, YScale;
FeatureSet = NewFeatureSet(MAX_PICO_FEATURES);
Outlines = ConvertBlob(Blob);
NormalizeOutlines(Outlines, &XScale, &YScale);
RemainingOutlines = Outlines;
iterate(RemainingOutlines)
{
Outline = (MFOUTLINE) first_node(RemainingOutlines);
ConvertToPicoFeatures2(Outline, FeatureSet);
}
if (classify_norm_method == baseline)
NormalizePicoX(FeatureSet);
FreeOutlines(Outlines);
return (FeatureSet);
} /* ExtractPicoFeatures */
FEATURE_SET Classify::ExtractOutlineFeatures(TBLOB *Blob) {
/*
** Parameters:
** Blob blob to extract pico-features from
** LineStats statistics on text row blob is in
** Globals: none
** Operation: Convert each segment in the outline to a feature
** and return the features.
** Return: Outline-features for Blob.
** Exceptions: none
** History: 11/13/90, DSJ, Created.
** 05/24/91, DSJ, Updated for either char or baseline normalize.
*/
LIST Outlines;
LIST RemainingOutlines;
MFOUTLINE Outline;
FEATURE_SET FeatureSet;
FLOAT32 XScale, YScale;
FeatureSet = NewFeatureSet (MAX_OUTLINE_FEATURES);
if (Blob == NULL)
return (FeatureSet);
Outlines = ConvertBlob (Blob);
NormalizeOutlines(Outlines, &XScale, &YScale);
RemainingOutlines = Outlines;
iterate(RemainingOutlines) {
Outline = (MFOUTLINE) first_node (RemainingOutlines);
ConvertToOutlineFeatures(Outline, FeatureSet);
}
if (classify_norm_method == baseline)
NormalizeOutlineX(FeatureSet);
FreeOutlines(Outlines);
return (FeatureSet);
} /* ExtractOutlineFeatures */
/**
* This routine extracts micro-features from the specified
* blob and returns a list of the micro-features. All
* micro-features are normalized according to the specified
* line statistics.
* @param Blob blob to extract micro-features from
* @param cn_denorm control parameter to feature extractor
* @return List of micro-features extracted from the blob.
* @note Exceptions: none
* @note History: 7/21/89, DSJ, Created.
*/
MICROFEATURES BlobMicroFeatures(TBLOB* Blob, const DENORM& cn_denorm) {
MICROFEATURES MicroFeatures = NIL_LIST;
LIST Outlines;
LIST RemainingOutlines;
MFOUTLINE Outline;
if (Blob != nullptr) {
Outlines = ConvertBlob(Blob);
RemainingOutlines = Outlines;
iterate(RemainingOutlines) {
Outline = (MFOUTLINE) first_node (RemainingOutlines);
CharNormalizeOutline(Outline, cn_denorm);
}
RemainingOutlines = Outlines;
iterate(RemainingOutlines) {
Outline = (MFOUTLINE) first_node(RemainingOutlines);
FindDirectionChanges(Outline, classify_min_slope, classify_max_slope);
MarkDirectionChanges(Outline);
MicroFeatures = ConvertToMicroFeatures(Outline, MicroFeatures);
}
FreeOutlines(Outlines);
}
/*---------------------------------------------------------------------------*/
FEATURE_SET ExtractCharNormFeatures(TBLOB *Blob, LINE_STATS *LineStats) {
/*
** Parameters:
** Blob blob to extract char norm feature from
** LineStats statistics on text row blob is in
** Globals: none
** Operation: Compute a feature whose parameters describe how a
** character will be affected by the character normalization
** algorithm. The feature parameters are:
** y position of center of mass in baseline coordinates
** total length of outlines in baseline coordinates
** divided by a scale factor
** radii of gyration about the center of mass in
** baseline coordinates
** Return: Character normalization feature for Blob.
** Exceptions: none
** History: Wed May 23 18:06:38 1990, DSJ, Created.
*/
FEATURE_SET FeatureSet;
FEATURE Feature;
FLOAT32 Scale;
FLOAT32 Baseline;
LIST Outlines;
INT_FEATURE_ARRAY blfeatures;
INT_FEATURE_ARRAY cnfeatures;
INT_FX_RESULT_STRUCT FXInfo;
/* allocate the feature and feature set - note that there is always one
and only one char normalization feature for any blob */
FeatureSet = NewFeatureSet (1);
Feature = NewFeature (&CharNormDesc);
AddFeature(FeatureSet, Feature);
/* compute the normalization statistics for this blob */
Outlines = ConvertBlob (Blob);
/*---------Debug--------------------------------------------------*
OFile = fopen ("f:/ims/debug/nfOutline.logCPP", "r");
if (OFile == NULL)
{
OFile = Efopen ("f:/ims/debug/nfOutline.logCPP", "w");
WriteOutlines(OFile, Outlines);
}
else
{
fclose (OFile);
OFile = Efopen ("f:/ims/debug/nfOutline.logCPP", "a");
}
WriteOutlines(OFile, Outlines);
fclose (OFile);
*--------------------------------------------------------------------*/
ExtractIntFeat(Blob, blfeatures, cnfeatures, &FXInfo);
Baseline = BaselineAt (LineStats, FXInfo.Xmean);
Scale = ComputeScaleFactor (LineStats);
Feature->Params[CharNormY] = (FXInfo.Ymean - Baseline) * Scale;
Feature->Params[CharNormLength] =
FXInfo.Length * Scale / LENGTH_COMPRESSION;
Feature->Params[CharNormRx] = FXInfo.Rx * Scale;
Feature->Params[CharNormRy] = FXInfo.Ry * Scale;
/*---------Debug--------------------------------------------------*
File = fopen ("f:/ims/debug/nfFeatSet.logCPP", "r");
if (File == NULL)
{
File = Efopen ("f:/ims/debug/nfFeatSet.logCPP", "w");
WriteFeatureSet(File, FeatureSet);
}
else
{
fclose (File);
File = Efopen ("f:/ims/debug/nfFeatSet.logCPP", "a");
}
WriteFeatureSet(File, FeatureSet);
fclose (File);
*--------------------------------------------------------------------*/
FreeOutlines(Outlines);
return (FeatureSet);
} /* ExtractCharNormFeatures */
/*---------------------------------------------------------------------------*/
FEATURE_SET ExtractPicoFeatures(TBLOB *Blob, LINE_STATS *LineStats) {
/*
** Parameters:
** Blob blob to extract pico-features from
** LineStats statistics on text row blob is in
** Globals:
** classify_norm_method normalization method currently specified
** Operation: Dummy for now.
** Return: Pico-features for Blob.
** Exceptions: none
** History: 9/4/90, DSJ, Created.
*/
LIST Outlines;
LIST RemainingOutlines;
MFOUTLINE Outline;
FEATURE_SET FeatureSet;
FLOAT32 XScale, YScale;
FeatureSet = NewFeatureSet (MAX_PICO_FEATURES);
Outlines = ConvertBlob (Blob);
NormalizeOutlines(Outlines, LineStats, &XScale, &YScale);
RemainingOutlines = Outlines;
iterate(RemainingOutlines) {
Outline = (MFOUTLINE) first_node (RemainingOutlines);
/*---------Debug--------------------------------------------------*
OFile = fopen ("f:/ims/debug/pfOutline.logCPP", "r");
if (OFile == NULL)
{
OFile = Efopen ("f:/ims/debug/pfOutline.logCPP", "w");
WriteOutline(OFile, Outline);
}
else
{
fclose (OFile);
OFile = Efopen ("f:/ims/debug/pfOutline.logCPP", "a");
}
WriteOutline(OFile, Outline);
fclose (OFile);
*--------------------------------------------------------------------*/
ConvertToPicoFeatures2(Outline, FeatureSet);
}
if (classify_norm_method == baseline)
NormalizePicoX(FeatureSet);
/*---------Debug--------------------------------------------------*
File = fopen ("f:/ims/debug/pfFeatSet.logCPP", "r");
if (File == NULL)
{
File = Efopen ("f:/ims/debug/pfFeatSet.logCPP", "w");
WriteFeatureSet(File, FeatureSet);
}
else
{
fclose (File);
File = Efopen ("f:/ims/debug/pfFeatSet.logCPP", "a");
}
WriteFeatureSet(File, FeatureSet);
fclose (File);
*--------------------------------------------------------------------*/
FreeOutlines(Outlines);
return (FeatureSet);
} /* ExtractPicoFeatures */
