Scene Text Recognition

Classes
class	cv::text::BaseOCR
class	cv::text::OCRHMMDecoder
	OCRHMMDecoder class provides an interface for OCR using Hidden Markov Models. More...
class	cv::text::OCRTesseract
	OCRTesseract class provides an interface with the tesseract-ocr API (v3.02.02) in C++. More...

Enumerations
enum	{   cv::text::OCR_LEVEL_WORD,   cv::text::OCR_LEVEL_TEXTLINE }
enum	cv::text::classifier_type {   cv::text::OCR_KNN_CLASSIFIER = 0,   cv::text::OCR_CNN_CLASSIFIER = 1 }
enum	cv::text::decoder_mode { cv::text::OCR_DECODER_VITERBI = 0 }
enum	cv::text::ocr_engine_mode {   cv::text::OEM_TESSERACT_ONLY,   cv::text::OEM_CUBE_ONLY,   cv::text::OEM_TESSERACT_CUBE_COMBINED,   cv::text::OEM_DEFAULT }
	Tesseract.OcrEngineMode Enumeration. More...
enum	cv::text::page_seg_mode {   cv::text::PSM_OSD_ONLY,   cv::text::PSM_AUTO_OSD,   cv::text::PSM_AUTO_ONLY,   cv::text::PSM_AUTO,   cv::text::PSM_SINGLE_COLUMN,   cv::text::PSM_SINGLE_BLOCK_VERT_TEXT,   cv::text::PSM_SINGLE_BLOCK,   cv::text::PSM_SINGLE_LINE,   cv::text::PSM_SINGLE_WORD,   cv::text::PSM_CIRCLE_WORD,   cv::text::PSM_SINGLE_CHAR }
	Tesseract.PageSegMode Enumeration. More...

Functions
Ptr< OCRHMMDecoder::ClassifierCallback >	cv::text::loadOCRHMMClassifier (const String &filename, int classifier)
	Allow to implicitly load the default character classifier when creating an OCRHMMDecoder object. More...
Ptr< OCRHMMDecoder::ClassifierCallback >	cv::text::loadOCRHMMClassifierCNN (const String &filename)
	Allow to implicitly load the default character classifier when creating an OCRHMMDecoder object. More...
Ptr< OCRHMMDecoder::ClassifierCallback >	cv::text::loadOCRHMMClassifierNM (const String &filename)
	Allow to implicitly load the default character classifier when creating an OCRHMMDecoder object. More...

Detailed Description

Enumeration Type Documentation

anonymous enum

anonymous enum

Enumerator
OCR_LEVEL_WORD
OCR_LEVEL_TEXTLINE

classifier_type

enum cv::text::classifier_type

Enumerator
OCR_KNN_CLASSIFIER
OCR_CNN_CLASSIFIER

decoder_mode

enum cv::text::decoder_mode

Enumerator
OCR_DECODER_VITERBI

ocr_engine_mode

enum cv::text::ocr_engine_mode

Tesseract.OcrEngineMode Enumeration.

Enumerator
OEM_TESSERACT_ONLY
OEM_CUBE_ONLY
OEM_TESSERACT_CUBE_COMBINED
OEM_DEFAULT

page_seg_mode

enum cv::text::page_seg_mode

Tesseract.PageSegMode Enumeration.

Enumerator
PSM_OSD_ONLY
PSM_AUTO_OSD
PSM_AUTO_ONLY
PSM_AUTO
PSM_SINGLE_COLUMN
PSM_SINGLE_BLOCK_VERT_TEXT
PSM_SINGLE_BLOCK
PSM_SINGLE_LINE
PSM_SINGLE_WORD
PSM_CIRCLE_WORD
PSM_SINGLE_CHAR

Function Documentation

loadOCRHMMClassifier()

Ptr<OCRHMMDecoder::ClassifierCallback> cv::text::loadOCRHMMClassifier	(	const String &	filename,
		int	classifier
	)

Allow to implicitly load the default character classifier when creating an OCRHMMDecoder object.

Parameters

filename	The XML or YAML file with the classifier model (e.g. OCRBeamSearch_CNN_model_data.xml.gz)
classifier	Can be one of classifier_type enum values.

loadOCRHMMClassifierCNN()

Ptr<OCRHMMDecoder::ClassifierCallback> cv::text::loadOCRHMMClassifierCNN

(

const String &

filename

)

Allow to implicitly load the default character classifier when creating an OCRHMMDecoder object.

Parameters

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.

Deprecated:

use loadOCRHMMClassifier instead

loadOCRHMMClassifierNM()

Ptr<OCRHMMDecoder::ClassifierCallback> cv::text::loadOCRHMMClassifierNM

(

const String &

filename

)

Allow to implicitly load the default character classifier when creating an OCRHMMDecoder object.

Parameters

filename

The XML or YAML file with the classifier model (e.g. OCRHMM_knn_model_data.xml)

The KNN default classifier is based in the scene text recognition method proposed by Lukás Neumann & Jiri Matas in [Neumann11b]. Basically, the region (contour) in the input image is normalized to a fixed size, while retaining the centroid and aspect ratio, in order to extract a feature vector based on gradient orientations along the chain-code of its perimeter. Then, the region is classified using a KNN model trained with synthetic data of rendered characters with different standard font types.

Deprecated:

loadOCRHMMClassifier instead