do_ocr_single_class_knnT_do_ocr_single_class_knnDoOcrSingleClassKnnDoOcrSingleClassKnndo_ocr_single_class_knn (Operator)

Name

do_ocr_single_class_knnT_do_ocr_single_class_knnDoOcrSingleClassKnnDoOcrSingleClassKnndo_ocr_single_class_knn — Classify a single character with an OCR classifier.

Signature

do_ocr_single_class_knn(Character, Image : : OCRHandle, NumClasses, NumNeighbors : Class, Confidence)

Description

do_ocr_single_class_knndo_ocr_single_class_knnDoOcrSingleClassKnnDoOcrSingleClassKnnDoOcrSingleClassKnndo_ocr_single_class_knn uses the OCR-k-NN classifier OCRHandleOCRHandleOCRHandleOCRHandleOCRHandleocrhandle to determine the best training samples for the features of the character given by the region CharacterCharacterCharacterCharactercharactercharacter and the gray values ImageImageImageImageimageimage and returns their classes in ClassClassClassClassclassValclass and the corresponding confidences in ConfidenceConfidenceConfidenceConfidenceconfidenceconfidence. If the first NumNeighborsNumNeighborsNumNeighborsNumNeighborsnumNeighborsnum_neighbors training vectors have different classes, maximally NumClassesNumClassesNumClassesNumClassesnumClassesnum_classes classes are returned sorted by frequency and weighted distance. The confidences lie between 0.0 and 1.0. The larger the value, the more reliable is the classification. The confidence can be only computed robustly if NumNeighborsNumNeighborsNumNeighborsNumNeighborsnumNeighborsnum_neighbors is large enough.

Because multiple classes may be returned by do_ocr_single_class_knndo_ocr_single_class_knnDoOcrSingleClassKnnDoOcrSingleClassKnnDoOcrSingleClassKnndo_ocr_single_class_knn, CharacterCharacterCharacterCharactercharactercharacter may only contain a single region (a single character). If multiple characters should be classified in a single call, do_ocr_multi_class_knndo_ocr_multi_class_knnDoOcrMultiClassKnnDoOcrMultiClassKnnDoOcrMultiClassKnndo_ocr_multi_class_knn must be used. Before calling do_ocr_single_class_knndo_ocr_single_class_knnDoOcrSingleClassKnnDoOcrSingleClassKnnDoOcrSingleClassKnndo_ocr_single_class_knn, the classifier must be trained with trainf_ocr_class_knntrainf_ocr_class_knnTrainfOcrClassKnnTrainfOcrClassKnnTrainfOcrClassKnntrainf_ocr_class_knn or select_feature_set_trainf_knnselect_feature_set_trainf_knnSelectFeatureSetTrainfKnnSelectFeatureSetTrainfKnnSelectFeatureSetTrainfKnnselect_feature_set_trainf_knn. If all NumNeighborsNumNeighborsNumNeighborsNumNeighborsnumNeighborsnum_neighbors neighbors are of the same class, only one class is returned.

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

CharacterCharacterCharacterCharactercharactercharacter (input_object) region → object

Character to be recognized.

ImageImageImageImageimageimage (input_object) singlechannelimage → object (byte / uint2)

Gray values of the character.

OCRHandleOCRHandleOCRHandleOCRHandleOCRHandleocrhandle (input_control) ocr_knn → (handle)

Handle of the k-NN classifier.

NumClassesNumClassesNumClassesNumClassesnumClassesnum_classes (input_control) integer-array → (integer)

Number of maximal classes to determine.

Default value: 1

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

NumNeighborsNumNeighborsNumNeighborsNumNeighborsnumNeighborsnum_neighbors (input_control) integer-array → (integer)

Number of neighbors to consider.

Default value: 1

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

ClassClassClassClassclassValclass (output_control) string(-array) → (string)

Results of classifying the character with the k-NN.

ConfidenceConfidenceConfidenceConfidenceconfidenceconfidence (output_control) real(-array) → (real)

Confidence(s) of the class(es) of the character.

Result

If the parameters are valid, the operator do_ocr_single_class_knndo_ocr_single_class_knnDoOcrSingleClassKnnDoOcrSingleClassKnnDoOcrSingleClassKnndo_ocr_single_class_knn returns the value TRUE. If necessary, an exception is raised.