OpenCV
3.2.0
Open Source Computer Vision
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Classes | |
class | BaseOCR |
class | ERFilter |
Base class for 1st and 2nd stages of Neumann and Matas scene text detection algorithm [Neumann12]. : More... | |
struct | ERStat |
The ERStat structure represents a class-specific Extremal Region (ER). More... | |
class | OCRBeamSearchDecoder |
OCRBeamSearchDecoder class provides an interface for OCR using Beam Search algorithm. More... | |
class | OCRHMMDecoder |
OCRHMMDecoder class provides an interface for OCR using Hidden Markov Models. More... | |
class | OCRTesseract |
OCRTesseract class provides an interface with the tesseract-ocr API (v3.02.02) in C++. More... | |
Enumerations | |
enum | { ERFILTER_NM_RGBLGrad, ERFILTER_NM_IHSGrad } |
computeNMChannels operation modes More... | |
enum | { OCR_LEVEL_WORD, OCR_LEVEL_TEXTLINE } |
enum | decoder_mode { OCR_DECODER_VITERBI = 0 } |
enum | erGrouping_Modes { ERGROUPING_ORIENTATION_HORIZ, ERGROUPING_ORIENTATION_ANY } |
text::erGrouping operation modes More... | |
Functions | |
void | computeNMChannels (InputArray _src, OutputArrayOfArrays _channels, int _mode=ERFILTER_NM_RGBLGrad) |
Compute the different channels to be processed independently in the N&M algorithm [Neumann12]. More... | |
Ptr< ERFilter > | createERFilterNM1 (const Ptr< ERFilter::Callback > &cb, int thresholdDelta=1, float minArea=(float) 0.00025, float maxArea=(float) 0.13, float minProbability=(float) 0.4, bool nonMaxSuppression=true, float minProbabilityDiff=(float) 0.1) |
Create an Extremal Region Filter for the 1st stage classifier of N&M algorithm [Neumann12]. More... | |
Ptr< ERFilter > | createERFilterNM2 (const Ptr< ERFilter::Callback > &cb, float minProbability=(float) 0.3) |
Create an Extremal Region Filter for the 2nd stage classifier of N&M algorithm [Neumann12]. More... | |
void | createOCRHMMTransitionsTable (std::string &vocabulary, std::vector< std::string > &lexicon, OutputArray transition_probabilities_table) |
Utility function to create a tailored language model transitions table from a given list of words (lexicon). More... | |
Mat | createOCRHMMTransitionsTable (const String &vocabulary, std::vector< cv::String > &lexicon) |
void | detectRegions (InputArray image, const Ptr< ERFilter > &er_filter1, const Ptr< ERFilter > &er_filter2, std::vector< std::vector< Point > > ®ions) |
void | erGrouping (InputArray img, InputArrayOfArrays channels, std::vector< std::vector< ERStat > > ®ions, std::vector< std::vector< Vec2i > > &groups, std::vector< Rect > &groups_rects, int method=ERGROUPING_ORIENTATION_HORIZ, const std::string &filename=std::string(), float minProbablity=0.5) |
Find groups of Extremal Regions that are organized as text blocks. More... | |
void | erGrouping (InputArray image, InputArray channel, std::vector< std::vector< Point > > regions, std::vector< Rect > &groups_rects, int method=ERGROUPING_ORIENTATION_HORIZ, const String &filename=String(), float minProbablity=(float) 0.5) |
Ptr< ERFilter::Callback > | loadClassifierNM1 (const String &filename) |
Allow to implicitly load the default classifier when creating an ERFilter object. More... | |
Ptr< ERFilter::Callback > | loadClassifierNM2 (const String &filename) |
Allow to implicitly load the default classifier when creating an ERFilter object. More... | |
Ptr< OCRBeamSearchDecoder::ClassifierCallback > | loadOCRBeamSearchClassifierCNN (const String &filename) |
Allow to implicitly load the default character classifier when creating an OCRBeamSearchDecoder object. More... | |
Ptr< OCRHMMDecoder::ClassifierCallback > | loadOCRHMMClassifierCNN (const String &filename) |
Allow to implicitly load the default character classifier when creating an OCRHMMDecoder object. More... | |
Ptr< OCRHMMDecoder::ClassifierCallback > | loadOCRHMMClassifierNM (const String &filename) |
Allow to implicitly load the default character classifier when creating an OCRHMMDecoder object. More... | |
void | MSERsToERStats (InputArray image, std::vector< std::vector< Point > > &contours, std::vector< std::vector< ERStat > > ®ions) |
Converts MSER contours (vector<Point>) to ERStat regions. More... | |
void cv::text::createOCRHMMTransitionsTable | ( | std::string & | vocabulary, |
std::vector< std::string > & | lexicon, | ||
OutputArray | transition_probabilities_table | ||
) |
Utility function to create a tailored language model transitions table from a given list of words (lexicon).
vocabulary | The language vocabulary (chars when ascii english text). |
lexicon | The list of words that are expected to be found in a particular image. |
transition_probabilities_table | Output table with transition probabilities between character pairs. cols == rows == vocabulary.size(). |
The function calculate frequency statistics of character pairs from the given lexicon and fills the output transition_probabilities_table with them. The transition_probabilities_table can be used as input in the OCRHMMDecoder::create() and OCRBeamSearchDecoder::create() methods.
Mat cv::text::createOCRHMMTransitionsTable | ( | const String & | vocabulary, |
std::vector< cv::String > & | lexicon | ||
) |
Ptr<OCRBeamSearchDecoder::ClassifierCallback> cv::text::loadOCRBeamSearchClassifierCNN | ( | const String & | filename | ) |
Allow to implicitly load the default character classifier when creating an OCRBeamSearchDecoder object.
filename | The XML or YAML file with the classifier model (e.g. OCRBeamSearch_CNN_model_data.xml.gz) |
The CNN default classifier is based in the scene text recognition method proposed by Adam Coates & Andrew NG in [Coates11a]. The character classifier consists in a Single Layer Convolutional Neural Network and a linear classifier. It is applied to the input image in a sliding window fashion, providing a set of recognitions at each window location.