Operator Reference

HALCON Operator Reference / OCR / K-Nearest Neighbors
ClassesClasses | | Operators

do_ocr_word_knnT_do_ocr_word_knnDoOcrWordKnnDoOcrWordKnndo_ocr_word_knn (Operator)

do_ocr_word_knnT_do_ocr_word_knnDoOcrWordKnnDoOcrWordKnndo_ocr_word_knn — Classify a related group of characters with an OCR classifier.

Signature

Herror T_do_ocr_word_knn(const Hobject Character, const Hobject Image, const Htuple OCRHandle, const Htuple Expression, const Htuple NumAlternatives, const Htuple NumCorrections, Htuple* Class, Htuple* Confidence, Htuple* Word, Htuple* Score)

void DoOcrWordKnn(const HObject& Character, const HObject& Image, const HTuple& OCRHandle, const HTuple& Expression, const HTuple& NumAlternatives, const HTuple& NumCorrections, HTuple* Class, HTuple* Confidence, HTuple* Word, HTuple* Score)

HTuple HRegion::DoOcrWordKnn(const HImage& Image, const HOCRKnn& OCRHandle, const HString& Expression, Hlong NumAlternatives, Hlong NumCorrections, HTuple* Confidence, HString* Word, double* Score) const

HString HRegion::DoOcrWordKnn(const HImage& Image, const HOCRKnn& OCRHandle, const HString& Expression, Hlong NumAlternatives, Hlong NumCorrections, double* Confidence, HString* Word, double* Score) const

HString HRegion::DoOcrWordKnn(const HImage& Image, const HOCRKnn& OCRHandle, const char* Expression, Hlong NumAlternatives, Hlong NumCorrections, double* Confidence, HString* Word, double* Score) const

HString HRegion::DoOcrWordKnn(const HImage& Image, const HOCRKnn& OCRHandle, const wchar_t* Expression, Hlong NumAlternatives, Hlong NumCorrections, double* Confidence, HString* Word, double* Score) const   ( Windows only)

HTuple HOCRKnn::DoOcrWordKnn(const HRegion& Character, const HImage& Image, const HString& Expression, Hlong NumAlternatives, Hlong NumCorrections, HTuple* Confidence, HString* Word, double* Score) const

HString HOCRKnn::DoOcrWordKnn(const HRegion& Character, const HImage& Image, const HString& Expression, Hlong NumAlternatives, Hlong NumCorrections, double* Confidence, HString* Word, double* Score) const

HString HOCRKnn::DoOcrWordKnn(const HRegion& Character, const HImage& Image, const char* Expression, Hlong NumAlternatives, Hlong NumCorrections, double* Confidence, HString* Word, double* Score) const

HString HOCRKnn::DoOcrWordKnn(const HRegion& Character, const HImage& Image, const wchar_t* Expression, Hlong NumAlternatives, Hlong NumCorrections, double* Confidence, HString* Word, double* Score) const   ( Windows only)

static void HOperatorSet.DoOcrWordKnn(HObject character, HObject image, HTuple OCRHandle, HTuple expression, HTuple numAlternatives, HTuple numCorrections, out HTuple classVal, out HTuple confidence, out HTuple word, out HTuple score)

HTuple HRegion.DoOcrWordKnn(HImage image, HOCRKnn OCRHandle, string expression, int numAlternatives, int numCorrections, out HTuple confidence, out string word, out double score)

string HRegion.DoOcrWordKnn(HImage image, HOCRKnn OCRHandle, string expression, int numAlternatives, int numCorrections, out double confidence, out string word, out double score)

HTuple HOCRKnn.DoOcrWordKnn(HRegion character, HImage image, string expression, int numAlternatives, int numCorrections, out HTuple confidence, out string word, out double score)

string HOCRKnn.DoOcrWordKnn(HRegion character, HImage image, string expression, int numAlternatives, int numCorrections, out double confidence, out string word, out double score)

def do_ocr_word_knn(character: HObject, image: HObject, ocrhandle: HHandle, expression: str, num_alternatives: int, num_corrections: int) -> Tuple[Sequence[str], Sequence[float], str, float]

def do_ocr_word_knn_s(character: HObject, image: HObject, ocrhandle: HHandle, expression: str, num_alternatives: int, num_corrections: int) -> Tuple[str, float, str, float]

Description

do_ocr_word_knndo_ocr_word_knnDoOcrWordKnnDoOcrWordKnndo_ocr_word_knn works like do_ocr_multi_class_knndo_ocr_multi_class_knnDoOcrMultiClassKnnDoOcrMultiClassKnndo_ocr_multi_class_knn insofar as it computes the best class for each of the characters given by the regions CharacterCharacterCharactercharactercharacter and the gray values ImageImageImageimageimage with the OCR classifier OCRHandleOCRHandleOCRHandleOCRHandleocrhandle, and returns the classes in ClassClassClassclassValclass and the corresponding confidences of the classes in ConfidenceConfidenceConfidenceconfidenceconfidence. The confidences lie between 0.0 and 1.0. The larger the value, the more reliable is the classification of the single characters.

In contrast to do_ocr_multi_class_knndo_ocr_multi_class_knnDoOcrMultiClassKnnDoOcrMultiClassKnndo_ocr_multi_class_knn, do_ocr_word_knndo_ocr_word_knnDoOcrWordKnnDoOcrWordKnndo_ocr_word_knn treats the group of characters as an entity which yields a WordWordWordwordword by concatenating the class names for each character region. This allows to restrict the allowed classification results on a textual level by specifying an ExpressionExpressionExpressionexpressionexpression describing the expected word.

The ExpressionExpressionExpressionexpressionexpression may restrict the word to belong to a predefined lexicon created using create_lexiconcreate_lexiconCreateLexiconCreateLexiconcreate_lexicon or import_lexiconimport_lexiconImportLexiconImportLexiconimport_lexicon, by specifying the name of the lexicon in angular brackets as in '<mylexicon>'"<mylexicon>""<mylexicon>""<mylexicon>""<mylexicon>". If the ExpressionExpressionExpressionexpressionexpression is of any other form, it is interpreted as a regular expression with the same syntax as specified for tuple_regexp_matchtuple_regexp_matchTupleRegexpMatchTupleRegexpMatchtuple_regexp_match. Note that you will usually want to use an expression of the form '^...$' when using variable quantifiers like '*', to ensure that the entire word is used in the expression. Also note that in contrast to tuple_regexp_matchtuple_regexp_matchTupleRegexpMatchTupleRegexpMatchtuple_regexp_match, do_ocr_word_knndo_ocr_word_knnDoOcrWordKnnDoOcrWordKnndo_ocr_word_knn does not support passing extra options in an expression tuple.

If the word derived from the best class for each character does not match the ExpressionExpressionExpressionexpressionexpression, do_ocr_word_knndo_ocr_word_knnDoOcrWordKnnDoOcrWordKnndo_ocr_word_knn attempts to correct it by considering the NumAlternativesNumAlternativesNumAlternativesnumAlternativesnum_alternatives best classes for each character. The alternatives used are identical to those returned by do_ocr_single_class_knndo_ocr_single_class_knnDoOcrSingleClassKnnDoOcrSingleClassKnndo_ocr_single_class_knn for a single character. It does so by testing all possible corrections for which the classification result is changed for at most NumCorrectionsNumCorrectionsNumCorrectionsnumCorrectionsnum_corrections character regions. Note that NumAlternativesNumAlternativesNumAlternativesnumAlternativesnum_alternatives and NumCorrectionsNumCorrectionsNumCorrectionsnumCorrectionsnum_corrections affect the complexity of the algorithm, so that in some cases internal restrictions are made. See the section 'Complexity' below for further information.

In case the ExpressionExpressionExpressionexpressionexpression is a lexicon and the above procedure did not yield a result, the most similar word in the lexicon is returned as long as it requires less than NumCorrectionsNumCorrectionsNumCorrectionsnumCorrectionsnum_corrections edit operations for the correction (see suggest_lexiconsuggest_lexiconSuggestLexiconSuggestLexiconsuggest_lexicon).

The resulting word is graded by a ScoreScoreScorescorescore between 0.0 (no correction found) and 1.0 (original word correct). The ScoreScoreScorescorescore is lowered by adding a penalty according to the number of corrected characters and another (minor) penalty depending on how many classes with higher confidences have been ignored in order to match the ExpressionExpressionExpressionexpressionexpression:

with num_corr being the actual number of applied corrections and num_alt the total number of discarded alternatives.

Note that this is a combinatorial score which does not reflect the original ConfidenceConfidenceConfidenceconfidenceconfidence of the best ClassClassClassclassValclass.

Execution Information

  • Multithreading type: reentrant (runs in parallel with non-exclusive operators).
  • Multithreading scope: global (may be called from any thread).
  • Processed without parallelization.

Parameters

CharacterCharacterCharactercharactercharacter (input_object)  region(-array) → objectHRegionHObjectHObjectHobject

Characters to be recognized.

ImageImageImageimageimage (input_object)  singlechannelimage → objectHImageHObjectHObjectHobject (byte / uint2)

Gray values of the characters.

OCRHandleOCRHandleOCRHandleOCRHandleocrhandle (input_control)  ocr_knn → HOCRKnn, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

Handle of the OCR classifier.

ExpressionExpressionExpressionexpressionexpression (input_control)  string → HTuplestrHTupleHtuple (string) (string) (HString) (char*)

Expression describing the allowed word structure.

NumAlternativesNumAlternativesNumAlternativesnumAlternativesnum_alternatives (input_control)  integer → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Number of classes per character considered for the internal word correction.

Default: 3

Suggested values: 3, 4, 5

Value range: 1 ≤ NumAlternatives NumAlternatives NumAlternatives numAlternatives num_alternatives ≤ 5

NumCorrectionsNumCorrectionsNumCorrectionsnumCorrectionsnum_corrections (input_control)  integer → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Maximum number of corrected characters.

Default: 2

Suggested values: 1, 2, 3, 4, 5

Value range: 0 ≤ NumCorrections NumCorrections NumCorrections numCorrections num_corrections ≤ 5

ClassClassClassclassValclass (output_control)  string(-array) → HTupleSequence[str]HTupleHtuple (string) (string) (HString) (char*)

Result of classifying the characters with the k-NN.

Number of elements: Class == Character

ConfidenceConfidenceConfidenceconfidenceconfidence (output_control)  real(-array) → HTupleSequence[float]HTupleHtuple (real) (double) (double) (double)

Confidence of the class of the characters.

Number of elements: Confidence == Character

WordWordWordwordword (output_control)  string → HTuplestrHTupleHtuple (string) (string) (HString) (char*)

Word text after classification and correction.

ScoreScoreScorescorescore (output_control)  real → HTuplefloatHTupleHtuple (real) (double) (double) (double)

Measure of similarity between corrected word and uncorrected classification results.

Complexity

The complexity of checking all possible corrections is of magnitude , where a is the number of alternatives, n is the number of character regions, and c is the number of allowed corrections. However, to guard against a near-infinite loop in case of large n, c is internally clipped to 5, 3, or 1 if a*n >= 30, 60, or 90, respectively.

Result

If the parameters are valid, the operator do_ocr_word_knndo_ocr_word_knnDoOcrWordKnnDoOcrWordKnndo_ocr_word_knn returns the value 2 ( H_MSG_TRUE) . If necessary, an exception is raised.

Possible Predecessors

trainf_ocr_class_knntrainf_ocr_class_knnTrainfOcrClassKnnTrainfOcrClassKnntrainf_ocr_class_knn, read_ocr_class_knnread_ocr_class_knnReadOcrClassKnnReadOcrClassKnnread_ocr_class_knn

Alternatives

do_ocr_multi_class_knndo_ocr_multi_class_knnDoOcrMultiClassKnnDoOcrMultiClassKnndo_ocr_multi_class_knn

See also

create_ocr_class_knncreate_ocr_class_knnCreateOcrClassKnnCreateOcrClassKnncreate_ocr_class_knn, classify_class_knnclassify_class_knnClassifyClassKnnClassifyClassKnnclassify_class_knn

Module

OCR/OCV

ClassesClasses | | Operators