Name
create_ocr_class_mlpT_create_ocr_class_mlpCreateOcrClassMlpcreate_ocr_class_mlpCreateOcrClassMlpCreateOcrClassMlp — Create an OCR classifier using a multilayer perceptron.
Herror create_ocr_class_mlp(const HTuple& WidthCharacter, const HTuple& HeightCharacter, const HTuple& Interpolation, const HTuple& Features, const HTuple& Characters, const HTuple& NumHidden, const HTuple& Preprocessing, const HTuple& NumComponents, const HTuple& RandSeed, Hlong* OCRHandle)
void HOCRMlp::CreateOcrClassMlp(const HTuple& WidthCharacter, const HTuple& HeightCharacter, const HTuple& Interpolation, const HTuple& Features, const HTuple& Characters, const HTuple& NumHidden, const HTuple& Preprocessing, const HTuple& NumComponents, const HTuple& RandSeed)
void CreateOcrClassMlp(const HTuple& WidthCharacter, const HTuple& HeightCharacter, const HTuple& Interpolation, const HTuple& Features, const HTuple& Characters, const HTuple& NumHidden, const HTuple& Preprocessing, const HTuple& NumComponents, const HTuple& RandSeed, HTuple* OCRHandle)
void HOCRMlp::HOCRMlp(Hlong WidthCharacter, Hlong HeightCharacter, const HString& Interpolation, const HTuple& Features, const HTuple& Characters, Hlong NumHidden, const HString& Preprocessing, Hlong NumComponents, Hlong RandSeed)
void HOCRMlp::HOCRMlp(Hlong WidthCharacter, Hlong HeightCharacter, const HString& Interpolation, const HString& Features, const HTuple& Characters, Hlong NumHidden, const HString& Preprocessing, Hlong NumComponents, Hlong RandSeed)
void HOCRMlp::HOCRMlp(Hlong WidthCharacter, Hlong HeightCharacter, const char* Interpolation, const char* Features, const HTuple& Characters, Hlong NumHidden, const char* Preprocessing, Hlong NumComponents, Hlong RandSeed)
void HOCRMlp::CreateOcrClassMlp(Hlong WidthCharacter, Hlong HeightCharacter, const HString& Interpolation, const HTuple& Features, const HTuple& Characters, Hlong NumHidden, const HString& Preprocessing, Hlong NumComponents, Hlong RandSeed)
void HOCRMlp::CreateOcrClassMlp(Hlong WidthCharacter, Hlong HeightCharacter, const HString& Interpolation, const HString& Features, const HTuple& Characters, Hlong NumHidden, const HString& Preprocessing, Hlong NumComponents, Hlong RandSeed)
void HOCRMlp::CreateOcrClassMlp(Hlong WidthCharacter, Hlong HeightCharacter, const char* Interpolation, const char* Features, const HTuple& Characters, Hlong NumHidden, const char* Preprocessing, Hlong NumComponents, Hlong RandSeed)
void HOperatorSetX.CreateOcrClassMlp(
[in] VARIANT WidthCharacter, [in] VARIANT HeightCharacter, [in] VARIANT Interpolation, [in] VARIANT Features, [in] VARIANT Characters, [in] VARIANT NumHidden, [in] VARIANT Preprocessing, [in] VARIANT NumComponents, [in] VARIANT RandSeed, [out] VARIANT* OCRHandle)
void HOCRMlpX.CreateOcrClassMlp(
[in] Hlong WidthCharacter, [in] Hlong HeightCharacter, [in] BSTR Interpolation, [in] VARIANT Features, [in] VARIANT Characters, [in] Hlong NumHidden, [in] BSTR Preprocessing, [in] Hlong NumComponents, [in] Hlong RandSeed)
static void HOperatorSet.CreateOcrClassMlp(HTuple widthCharacter, HTuple heightCharacter, HTuple interpolation, HTuple features, HTuple characters, HTuple numHidden, HTuple preprocessing, HTuple numComponents, HTuple randSeed, out HTuple OCRHandle)
public HOCRMlp(int widthCharacter, int heightCharacter, string interpolation, HTuple features, HTuple characters, int numHidden, string preprocessing, int numComponents, int randSeed)
public HOCRMlp(int widthCharacter, int heightCharacter, string interpolation, string features, HTuple characters, int numHidden, string preprocessing, int numComponents, int randSeed)
void HOCRMlp.CreateOcrClassMlp(int widthCharacter, int heightCharacter, string interpolation, HTuple features, HTuple characters, int numHidden, string preprocessing, int numComponents, int randSeed)
void HOCRMlp.CreateOcrClassMlp(int widthCharacter, int heightCharacter, string interpolation, string features, HTuple characters, int numHidden, string preprocessing, int numComponents, int randSeed)
create_ocr_class_mlpcreate_ocr_class_mlpCreateOcrClassMlpcreate_ocr_class_mlpCreateOcrClassMlpCreateOcrClassMlp creates an OCR classifier that uses a
multilayer perceptron (MLP). The handle of the OCR classifier is
returned in OCRHandleOCRHandleOCRHandleOCRHandleOCRHandleOCRHandle.
For a description on how an MLP works, see create_class_mlpcreate_class_mlpCreateClassMlpcreate_class_mlpCreateClassMlpCreateClassMlp.
create_ocr_class_mlpcreate_ocr_class_mlpCreateOcrClassMlpcreate_ocr_class_mlpCreateOcrClassMlpCreateOcrClassMlp creates an MLP with
OutputFunction = 'softmax'"softmax""softmax""softmax""softmax""softmax". The length of the
feature vector of the MLP (NumInput in
create_class_mlpcreate_class_mlpCreateClassMlpcreate_class_mlpCreateClassMlpCreateClassMlp) is determined from the features that are
used for the OCR, which are passed in FeaturesFeaturesFeaturesFeaturesFeaturesfeatures. The
features are described below. The number of units in the hidden
layer is determined by NumHiddenNumHiddenNumHiddenNumHiddenNumHiddennumHidden. The number of output
variables of the MLP (NumOutput in
create_class_mlpcreate_class_mlpCreateClassMlpcreate_class_mlpCreateClassMlpCreateClassMlp) is determined from the names of the
characters to be used in the OCR, which are passed in
CharactersCharactersCharactersCharactersCharacterscharacters. As described with create_class_mlpcreate_class_mlpCreateClassMlpcreate_class_mlpCreateClassMlpCreateClassMlp,
the parameters PreprocessingPreprocessingPreprocessingPreprocessingPreprocessingpreprocessing and NumComponentsNumComponentsNumComponentsNumComponentsNumComponentsnumComponents can
be used to specify a preprocessing of the data (i.e., the feature
vectors). The OCR already approximately normalizes the features.
Hence, PreprocessingPreprocessingPreprocessingPreprocessingPreprocessingpreprocessing can typically be set to
'none'"none""none""none""none""none". The parameter RandSeedRandSeedRandSeedRandSeedRandSeedrandSeed has the same
meaning as in create_class_mlpcreate_class_mlpCreateClassMlpcreate_class_mlpCreateClassMlpCreateClassMlp.
The features to be used for the classification are determined by
FeaturesFeaturesFeaturesFeaturesFeaturesfeatures. FeaturesFeaturesFeaturesFeaturesFeaturesfeatures can contain a tuple of several
feature names. Each of these feature names results in one or more
features to be calculated for the classifier. Some of the feature
names compute gray value features (e.g., 'pixel_invar'"pixel_invar""pixel_invar""pixel_invar""pixel_invar""pixel_invar").
Because a classifier requires a constant number of features (input
variables), a character to be classified is transformed to a
standard size, which is determined by WidthCharacterWidthCharacterWidthCharacterWidthCharacterWidthCharacterwidthCharacter and
HeightCharacterHeightCharacterHeightCharacterHeightCharacterHeightCharacterheightCharacter. The interpolation to be used for the
transformation is determined by InterpolationInterpolationInterpolationInterpolationInterpolationinterpolation. It has the
same meaning as in affine_trans_imageaffine_trans_imageAffineTransImageaffine_trans_imageAffineTransImageAffineTransImage. The interpolation
should be chosen such that no aliasing effects occur in the
transformation. For most applications, InterpolationInterpolationInterpolationInterpolationInterpolationinterpolation =
'constant'"constant""constant""constant""constant""constant" should be used. It should be noted that the
size of the transformed character is not chosen too large, because
the generalization properties of the classifier may become bad for
large sizes. In particular, large sizes will lead to the fact that
small segmentation errors will have a large influence on the
computed features if gray value features are used. This happens
because segmentation errors will change the smallest enclosing
rectangle of the regions, which leads to the fact that the character
is zoomed differently than the characters in the training set. In
most applications, sizes between 6x8 and
10x14 should be used.
The parameter FeaturesFeaturesFeaturesFeaturesFeaturesfeatures can contain the following feature
names for the classification of the characters.
- 'default'"default""default""default""default""default"
-
'ratio'"ratio""ratio""ratio""ratio""ratio" and 'pixel_invar'"pixel_invar""pixel_invar""pixel_invar""pixel_invar""pixel_invar" are selected.
- 'pixel'"pixel""pixel""pixel""pixel""pixel"
-
Gray values of the character (WidthCharacterWidthCharacterWidthCharacterWidthCharacterWidthCharacterwidthCharacter x
HeightCharacterHeightCharacterHeightCharacterHeightCharacterHeightCharacterheightCharacter features).
- 'pixel_invar'"pixel_invar""pixel_invar""pixel_invar""pixel_invar""pixel_invar"
-
Gray values of the character with maximum scaling of the gray
values (WidthCharacterWidthCharacterWidthCharacterWidthCharacterWidthCharacterwidthCharacter x HeightCharacterHeightCharacterHeightCharacterHeightCharacterHeightCharacterheightCharacter
features).
- 'pixel_binary'"pixel_binary""pixel_binary""pixel_binary""pixel_binary""pixel_binary"
-
Region of the character as a binary image zoomed to a size of
WidthCharacterWidthCharacterWidthCharacterWidthCharacterWidthCharacterwidthCharacter x HeightCharacterHeightCharacterHeightCharacterHeightCharacterHeightCharacterheightCharacter
(WidthCharacterWidthCharacterWidthCharacterWidthCharacterWidthCharacterwidthCharacter x HeightCharacterHeightCharacterHeightCharacterHeightCharacterHeightCharacterheightCharacter
features).
- 'gradient_8dir'"gradient_8dir""gradient_8dir""gradient_8dir""gradient_8dir""gradient_8dir"
-
Gradients are computed on the character image. The gradient
directions are discretized into 8 directions. The amplitude image
is decomposed into 8 channels according to these discretized
directions. 25 samples on a 5x5 grid are extracted from
each channel. These samples are used as features (200 features).
- 'projection_horizontal'"projection_horizontal""projection_horizontal""projection_horizontal""projection_horizontal""projection_horizontal"
-
Horizontal projection of the gray values (see
gray_projectionsgray_projectionsGrayProjectionsgray_projectionsGrayProjectionsGrayProjections, HeightCharacterHeightCharacterHeightCharacterHeightCharacterHeightCharacterheightCharacter features).
- 'projection_horizontal_invar'"projection_horizontal_invar""projection_horizontal_invar""projection_horizontal_invar""projection_horizontal_invar""projection_horizontal_invar"
-
Maximally scaled horizontal projection of the gray values
(HeightCharacterHeightCharacterHeightCharacterHeightCharacterHeightCharacterheightCharacter features).
- 'projection_vertical'"projection_vertical""projection_vertical""projection_vertical""projection_vertical""projection_vertical"
-
Vertical projection of the gray values (see
gray_projectionsgray_projectionsGrayProjectionsgray_projectionsGrayProjectionsGrayProjections, WidthCharacterWidthCharacterWidthCharacterWidthCharacterWidthCharacterwidthCharacter features).
- 'projection_vertical_invar'"projection_vertical_invar""projection_vertical_invar""projection_vertical_invar""projection_vertical_invar""projection_vertical_invar"
-
Maximally scaled vertical projection of the gray values
(WidthCharacterWidthCharacterWidthCharacterWidthCharacterWidthCharacterwidthCharacter features).
- 'ratio'"ratio""ratio""ratio""ratio""ratio"
-
Aspect ratio of the character (1 feature).
- 'anisometry'"anisometry""anisometry""anisometry""anisometry""anisometry"
-
Anisometry of the character (see eccentricityeccentricityEccentricityeccentricityEccentricityEccentricity, 1 feature).
- 'width'"width""width""width""width""width"
-
Width of the character before scaling the character to the standard
size (not scale-invariant, see smallest_rectangle1smallest_rectangle1SmallestRectangle1smallest_rectangle1SmallestRectangle1SmallestRectangle1, 1
feature).
- 'height'"height""height""height""height""height"
-
Height of the character before scaling the character to the
standard size (not scale-invariant, see
smallest_rectangle1smallest_rectangle1SmallestRectangle1smallest_rectangle1SmallestRectangle1SmallestRectangle1, 1 feature).
- 'zoom_factor'"zoom_factor""zoom_factor""zoom_factor""zoom_factor""zoom_factor"
-
Difference in size between the character and the values of
WidthCharacterWidthCharacterWidthCharacterWidthCharacterWidthCharacterwidthCharacter and HeightCharacterHeightCharacterHeightCharacterHeightCharacterHeightCharacterheightCharacter (not
scale-invariant, 1 feature).
- 'foreground'"foreground""foreground""foreground""foreground""foreground"
-
Fraction of pixels in the foreground (1 feature).
- 'foreground_grid_9'"foreground_grid_9""foreground_grid_9""foreground_grid_9""foreground_grid_9""foreground_grid_9"
-
Fraction of pixels in the foreground in a 3x3 grid within
the smallest enclosing rectangle of the character (9 features).
- 'foreground_grid_16'"foreground_grid_16""foreground_grid_16""foreground_grid_16""foreground_grid_16""foreground_grid_16"
-
Fraction of pixels in the foreground in a 4x4 grid within
the smallest enclosing rectangle of the character (16 features).
- 'compactness'"compactness""compactness""compactness""compactness""compactness"
-
Compactness of the character (see compactnesscompactnessCompactnesscompactnessCompactnessCompactness, 1 feature).
- 'convexity'"convexity""convexity""convexity""convexity""convexity"
-
Convexity of the character (see convexityconvexityConvexityconvexityConvexityConvexity, 1 feature).
- 'moments_region_2nd_invar'"moments_region_2nd_invar""moments_region_2nd_invar""moments_region_2nd_invar""moments_region_2nd_invar""moments_region_2nd_invar"
-
Normalized 2nd moments of the character (see
moments_region_2nd_invarmoments_region_2nd_invarMomentsRegion2ndInvarmoments_region_2nd_invarMomentsRegion2ndInvarMomentsRegion2ndInvar, 3 features).
- 'moments_region_2nd_rel_invar'"moments_region_2nd_rel_invar""moments_region_2nd_rel_invar""moments_region_2nd_rel_invar""moments_region_2nd_rel_invar""moments_region_2nd_rel_invar"
-
Normalized 2nd relative moments of the character (see
moments_region_2nd_rel_invarmoments_region_2nd_rel_invarMomentsRegion2ndRelInvarmoments_region_2nd_rel_invarMomentsRegion2ndRelInvarMomentsRegion2ndRelInvar, 2 features).
- 'moments_region_3rd_invar'"moments_region_3rd_invar""moments_region_3rd_invar""moments_region_3rd_invar""moments_region_3rd_invar""moments_region_3rd_invar"
-
Normalized 3rd moments of the character (see
moments_region_3rd_invarmoments_region_3rd_invarMomentsRegion3rdInvarmoments_region_3rd_invarMomentsRegion3rdInvarMomentsRegion3rdInvar, 4 features).
- 'moments_central'"moments_central""moments_central""moments_central""moments_central""moments_central"
-
Normalized central moments of the character (see
moments_region_centralmoments_region_centralMomentsRegionCentralmoments_region_centralMomentsRegionCentralMomentsRegionCentral, 4 features).
- 'moments_gray_plane'"moments_gray_plane""moments_gray_plane""moments_gray_plane""moments_gray_plane""moments_gray_plane"
-
Normalized gray value moments and the angle of the gray value
plane (see moments_gray_planemoments_gray_planeMomentsGrayPlanemoments_gray_planeMomentsGrayPlaneMomentsGrayPlane, 4 features).
- 'phi'"phi""phi""phi""phi""phi"
-
Sinus and cosinus of the orientation (angle) of the character
(see elliptic_axiselliptic_axisEllipticAxiselliptic_axisEllipticAxisEllipticAxis, 2 feature).
- 'num_connect'"num_connect""num_connect""num_connect""num_connect""num_connect"
-
Number of connected components (see connect_and_holesconnect_and_holesConnectAndHolesconnect_and_holesConnectAndHolesConnectAndHoles, 1
feature).
- 'num_holes'"num_holes""num_holes""num_holes""num_holes""num_holes"
-
Number of holes (see connect_and_holesconnect_and_holesConnectAndHolesconnect_and_holesConnectAndHolesConnectAndHoles, 1 feature).
- 'cooc'"cooc""cooc""cooc""cooc""cooc"
-
Values of the binary cooccurrence matrix (see
gen_cooc_matrixgen_cooc_matrixGenCoocMatrixgen_cooc_matrixGenCoocMatrixGenCoocMatrix, 8 features).
- 'num_runs'"num_runs""num_runs""num_runs""num_runs""num_runs"
-
Number of runs in the region normalized by the height (1 feature).
- 'chord_histo'"chord_histo""chord_histo""chord_histo""chord_histo""chord_histo"
-
Frequency of the runs per row (HeightCharacterHeightCharacterHeightCharacterHeightCharacterHeightCharacterheightCharacter features).
After the classifier has been created, it is trained using
trainf_ocr_class_mlptrainf_ocr_class_mlpTrainfOcrClassMlptrainf_ocr_class_mlpTrainfOcrClassMlpTrainfOcrClassMlp. After this, the classifier can be
saved using write_ocr_class_mlpwrite_ocr_class_mlpWriteOcrClassMlpwrite_ocr_class_mlpWriteOcrClassMlpWriteOcrClassMlp. Alternatively, the
classifier can be used immediately after training to classify
characters using do_ocr_single_class_mlpdo_ocr_single_class_mlpDoOcrSingleClassMlpdo_ocr_single_class_mlpDoOcrSingleClassMlpDoOcrSingleClassMlp or
do_ocr_multi_class_mlpdo_ocr_multi_class_mlpDoOcrMultiClassMlpdo_ocr_multi_class_mlpDoOcrMultiClassMlpDoOcrMultiClassMlp.
HALCON provides a number of pretrained OCR classifiers (see Solution Guide
I, chapter 'OCR', section 'Pretrained OCR Fonts'). These pretrained OCR
classifiers can be read directly with read_ocr_class_mlpread_ocr_class_mlpReadOcrClassMlpread_ocr_class_mlpReadOcrClassMlpReadOcrClassMlp and make it
possible to read a wide variety of different fonts without the need to train
an OCR classifier. Therefore, it is recommended to try if one of the
pretrained OCR classifiers can be used successfully. If this is the case, it
is not necessary to create and train an OCR classifier.
A comparison of the MLP and the support vector machine (SVM) (see
create_ocr_class_svmcreate_ocr_class_svmCreateOcrClassSvmcreate_ocr_class_svmCreateOcrClassSvmCreateOcrClassSvm) typically shows that SVMs are
generally faster at training, especially for huge training sets, and
achieve slightly better recognition rates than MLPs. The MLP is
faster at classification and should therefore be prefered in time
critical applications. Please note that this guideline assumes
optimal tuning of the parameters.
- Multithreading type: exclusive (runs in parallel only with independent operators).
- Multithreading scope: global (may be called from any thread).
- Processed without parallelization.
Width of the rectangle to which the gray values
of the segmented character are zoomed.
Default value: 8
Suggested values: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16, 20
Typical range of values: 4
≤
WidthCharacter
WidthCharacter
WidthCharacter
WidthCharacter
WidthCharacter
widthCharacter
≤
20
Height of the rectangle to which the gray values
of the segmented character are zoomed.
Default value: 10
Suggested values: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16, 20
Typical range of values: 4
≤
HeightCharacter
HeightCharacter
HeightCharacter
HeightCharacter
HeightCharacter
heightCharacter
≤
20
Interpolation mode for the zooming of the characters.
Default value:
'constant'
"constant"
"constant"
"constant"
"constant"
"constant"
List of values: 'bilinear'"bilinear""bilinear""bilinear""bilinear""bilinear", 'constant'"constant""constant""constant""constant""constant", 'nearest_neighbor'"nearest_neighbor""nearest_neighbor""nearest_neighbor""nearest_neighbor""nearest_neighbor", 'weighted'"weighted""weighted""weighted""weighted""weighted"
Features to be used for classification.
Default value:
'default'
"default"
"default"
"default"
"default"
"default"
List of values: 'anisometry'"anisometry""anisometry""anisometry""anisometry""anisometry", 'chord_histo'"chord_histo""chord_histo""chord_histo""chord_histo""chord_histo", 'compactness'"compactness""compactness""compactness""compactness""compactness", 'convexity'"convexity""convexity""convexity""convexity""convexity", 'cooc'"cooc""cooc""cooc""cooc""cooc", 'default'"default""default""default""default""default", 'foreground'"foreground""foreground""foreground""foreground""foreground", 'foreground_grid_16'"foreground_grid_16""foreground_grid_16""foreground_grid_16""foreground_grid_16""foreground_grid_16", 'foreground_grid_9'"foreground_grid_9""foreground_grid_9""foreground_grid_9""foreground_grid_9""foreground_grid_9", 'gradient_8dir'"gradient_8dir""gradient_8dir""gradient_8dir""gradient_8dir""gradient_8dir", 'height'"height""height""height""height""height", 'moments_central'"moments_central""moments_central""moments_central""moments_central""moments_central", 'moments_gray_plane'"moments_gray_plane""moments_gray_plane""moments_gray_plane""moments_gray_plane""moments_gray_plane", 'moments_region_2nd_invar'"moments_region_2nd_invar""moments_region_2nd_invar""moments_region_2nd_invar""moments_region_2nd_invar""moments_region_2nd_invar", 'moments_region_2nd_rel_invar'"moments_region_2nd_rel_invar""moments_region_2nd_rel_invar""moments_region_2nd_rel_invar""moments_region_2nd_rel_invar""moments_region_2nd_rel_invar", 'moments_region_3rd_invar'"moments_region_3rd_invar""moments_region_3rd_invar""moments_region_3rd_invar""moments_region_3rd_invar""moments_region_3rd_invar", 'num_connect'"num_connect""num_connect""num_connect""num_connect""num_connect", 'num_holes'"num_holes""num_holes""num_holes""num_holes""num_holes", 'num_runs'"num_runs""num_runs""num_runs""num_runs""num_runs", 'phi'"phi""phi""phi""phi""phi", 'pixel'"pixel""pixel""pixel""pixel""pixel", 'pixel_binary'"pixel_binary""pixel_binary""pixel_binary""pixel_binary""pixel_binary", 'pixel_invar'"pixel_invar""pixel_invar""pixel_invar""pixel_invar""pixel_invar", 'projection_horizontal'"projection_horizontal""projection_horizontal""projection_horizontal""projection_horizontal""projection_horizontal", 'projection_horizontal_invar'"projection_horizontal_invar""projection_horizontal_invar""projection_horizontal_invar""projection_horizontal_invar""projection_horizontal_invar", 'projection_vertical'"projection_vertical""projection_vertical""projection_vertical""projection_vertical""projection_vertical", 'projection_vertical_invar'"projection_vertical_invar""projection_vertical_invar""projection_vertical_invar""projection_vertical_invar""projection_vertical_invar", 'ratio'"ratio""ratio""ratio""ratio""ratio", 'width'"width""width""width""width""width", 'zoom_factor'"zoom_factor""zoom_factor""zoom_factor""zoom_factor""zoom_factor"
All characters of the character set to be read.
Default value:
['0','1','2','3','4','5','6','7','8','9']
["0","1","2","3","4","5","6","7","8","9"]
["0","1","2","3","4","5","6","7","8","9"]
["0","1","2","3","4","5","6","7","8","9"]
["0","1","2","3","4","5","6","7","8","9"]
["0","1","2","3","4","5","6","7","8","9"]
Number of hidden units of the MLP.
Default value: 80
Suggested values: 1, 2, 3, 4, 5, 8, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 150
Restriction: NumHidden >= 1
Type of preprocessing used to transform the
feature vectors.
Default value:
'none'
"none"
"none"
"none"
"none"
"none"
List of values: 'canonical_variates'"canonical_variates""canonical_variates""canonical_variates""canonical_variates""canonical_variates", 'none'"none""none""none""none""none", 'normalization'"normalization""normalization""normalization""normalization""normalization", 'principal_components'"principal_components""principal_components""principal_components""principal_components""principal_components"
Preprocessing parameter: Number of transformed
features (ignored for PreprocessingPreprocessingPreprocessingPreprocessingPreprocessingpreprocessing =
'none'"none""none""none""none""none" and PreprocessingPreprocessingPreprocessingPreprocessingPreprocessingpreprocessing =
'normalization'"normalization""normalization""normalization""normalization""normalization").
Default value: 10
Suggested values: 1, 2, 3, 4, 5, 8, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100
Restriction: NumComponents >= 1
Seed value of the random number generator that
is used to initialize the MLP with random values.
Default value: 42
Handle of the OCR classifier.
read_image (Image, 'letters')
* Segment the image.
bin_threshold (Image, Region)
dilation_circle (Region, RegionDilation, 3.5)
connection (RegionDilation, ConnectedRegions)
intersection (ConnectedRegions, Region, RegionIntersection)
sort_region (RegionIntersection, Characters, 'character', 'true', 'row')
* Generate the training file.
count_obj (Characters, Number)
Classes := []
for J := 0 to 25 by 1
Classes := [Classes,gen_tuple_const(20,chr(ord('a')+J))]
endfor
Classes := [Classes,gen_tuple_const(20,'.')]
write_ocr_trainf (Characters, Image, Classes, 'letters.trf')
* Generate and train the classifier.
read_ocr_trainf_names ('letters.trf', CharacterNames, CharacterCount)
create_ocr_class_mlp (8, 10, 'constant', 'default', CharacterNames, 20, \
'none', 81, 42, OCRHandle)
trainf_ocr_class_mlp (OCRHandle, 'letters.trf', 100, 0.01, 0.01, Error, \
ErrorLog)
* Re-classify the characters in the image.
do_ocr_multi_class_mlp (Characters, Image, OCRHandle, Class, Confidence)
clear_ocr_class_mlp (OCRHandle)
If the parameters are valid, the operator
create_ocr_class_mlpcreate_ocr_class_mlpCreateOcrClassMlpcreate_ocr_class_mlpCreateOcrClassMlpCreateOcrClassMlp returns the value 2 (H_MSG_TRUE). If necessary,
an exception is raised.
trainf_ocr_class_mlptrainf_ocr_class_mlpTrainfOcrClassMlptrainf_ocr_class_mlpTrainfOcrClassMlpTrainfOcrClassMlp
create_ocr_class_svmcreate_ocr_class_svmCreateOcrClassSvmcreate_ocr_class_svmCreateOcrClassSvmCreateOcrClassSvm,
create_ocr_class_boxcreate_ocr_class_boxCreateOcrClassBoxcreate_ocr_class_boxCreateOcrClassBoxCreateOcrClassBox
do_ocr_single_class_mlpdo_ocr_single_class_mlpDoOcrSingleClassMlpdo_ocr_single_class_mlpDoOcrSingleClassMlpDoOcrSingleClassMlp,
do_ocr_multi_class_mlpdo_ocr_multi_class_mlpDoOcrMultiClassMlpdo_ocr_multi_class_mlpDoOcrMultiClassMlpDoOcrMultiClassMlp,
clear_ocr_class_mlpclear_ocr_class_mlpClearOcrClassMlpclear_ocr_class_mlpClearOcrClassMlpClearOcrClassMlp,
create_class_mlpcreate_class_mlpCreateClassMlpcreate_class_mlpCreateClassMlpCreateClassMlp,
train_class_mlptrain_class_mlpTrainClassMlptrain_class_mlpTrainClassMlpTrainClassMlp,
classify_class_mlpclassify_class_mlpClassifyClassMlpclassify_class_mlpClassifyClassMlpClassifyClassMlp
OCR/OCV