OpenCV
3.0.0
Open Source Computer Vision
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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::decoder_mode { cv::text::OCR_DECODER_VITERBI = 0 } |
Functions | |
Ptr < OCRHMMDecoder::ClassifierCallback > | cv::text::loadOCRHMMClassifierNM (const std::string &filename) |
Allow to implicitly load the default character classifier when creating an OCRHMMDecoder object. More... | |
Ptr<OCRHMMDecoder::ClassifierCallback> cv::text::loadOCRHMMClassifierNM | ( | const std::string & | filename | ) |
Allow to implicitly load the default character classifier when creating an OCRHMMDecoder object.
filename | The XML or YAML file with the classifier model (e.g. OCRHMM_knn_model_data.xml) |
The 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.