do_ocr_word_knnT_do_ocr_word_knnDoOcrWordKnnDoOcrWordKnn (Operator)

Name

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

Signature

Description

do_ocr_word_knndo_ocr_word_knnDoOcrWordKnnDoOcrWordKnnDoOcrWordKnn works like do_ocr_multi_class_knndo_ocr_multi_class_knnDoOcrMultiClassKnnDoOcrMultiClassKnnDoOcrMultiClassKnn 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 ClassClassClassClassclassVal 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_knnDoOcrMultiClassKnnDoOcrMultiClassKnnDoOcrMultiClassKnn, do_ocr_word_knndo_ocr_word_knnDoOcrWordKnnDoOcrWordKnnDoOcrWordKnn 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_lexiconCreateLexiconCreateLexiconCreateLexicon or import_lexiconimport_lexiconImportLexiconImportLexiconImportLexicon, 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_matchTupleRegexpMatchTupleRegexpMatchTupleRegexpMatch. 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_matchTupleRegexpMatchTupleRegexpMatchTupleRegexpMatch, do_ocr_word_knndo_ocr_word_knnDoOcrWordKnnDoOcrWordKnnDoOcrWordKnn 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_knnDoOcrWordKnnDoOcrWordKnnDoOcrWordKnn attempts to correct it by considering the NumAlternativesNumAlternativesNumAlternativesNumAlternativesnumAlternatives best classes for each character. The alternatives used are identical to those returned by do_ocr_single_class_knndo_ocr_single_class_knnDoOcrSingleClassKnnDoOcrSingleClassKnnDoOcrSingleClassKnn for a single character. It does so by testing all possible corrections for which the classification result is changed for at most NumCorrectionsNumCorrectionsNumCorrectionsNumCorrectionsnumCorrections character regions. Note that NumAlternativesNumAlternativesNumAlternativesNumAlternativesnumAlternatives and NumCorrectionsNumCorrectionsNumCorrectionsNumCorrectionsnumCorrections 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 NumCorrectionsNumCorrectionsNumCorrectionsNumCorrectionsnumCorrections edit operations for the correction (see suggest_lexiconsuggest_lexiconSuggestLexiconSuggestLexiconSuggestLexicon).

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 ClassClassClassClassclassVal.

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

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_knnDoOcrWordKnnDoOcrWordKnnDoOcrWordKnn returns the value 2 (H_MSG_TRUE). If necessary, an exception is raised.

Possible Predecessors

trainf_ocr_class_knntrainf_ocr_class_knnTrainfOcrClassKnnTrainfOcrClassKnnTrainfOcrClassKnn, read_ocr_class_knnread_ocr_class_knnReadOcrClassKnnReadOcrClassKnnReadOcrClassKnn

Alternatives

do_ocr_multi_class_knndo_ocr_multi_class_knnDoOcrMultiClassKnnDoOcrMultiClassKnnDoOcrMultiClassKnn

See also

create_ocr_class_knncreate_ocr_class_knnCreateOcrClassKnnCreateOcrClassKnnCreateOcrClassKnn, classify_class_knnclassify_class_knnClassifyClassKnnClassifyClassKnnClassifyClassKnn

Module

OCR/OCV