Class OCRHMMDecoder


  • public class OCRHMMDecoder
    extends BaseOCR
    OCRHMMDecoder class provides an interface for OCR using Hidden Markov Models. Note:
    • (C++) An example on using OCRHMMDecoder recognition combined with scene text detection can be found at the webcam_demo sample: <https://github.com/opencv/opencv_contrib/blob/master/modules/text/samples/webcam_demo.cpp>
    • Constructor Detail

      • OCRHMMDecoder

        protected OCRHMMDecoder​(long addr)
    • Method Detail

      • __fromPtr__

        public static OCRHMMDecoder __fromPtr__​(long addr)
      • run

        public String run​(Mat image,
                          int min_confidence,
                          int component_level)
        Recognize text using HMM. Takes an image and a mask (where each connected component corresponds to a segmented character) on input and returns recognized text in the output_text parameter. Optionally provides also the Rects for individual text elements found (e.g. words), and the list of those text elements with their confidence values.
        Parameters:
        image - Input image CV_8UC1 or CV_8UC3 with a single text line (or word). text elements found (e.g. words). recognition of individual text elements found (e.g. words). for the recognition of individual text elements found (e.g. words).
        component_level - Only OCR_LEVEL_WORD is supported.
        min_confidence - automatically generated
        Returns:
        automatically generated
      • run

        public String run​(Mat image,
                          int min_confidence)
        Recognize text using HMM. Takes an image and a mask (where each connected component corresponds to a segmented character) on input and returns recognized text in the output_text parameter. Optionally provides also the Rects for individual text elements found (e.g. words), and the list of those text elements with their confidence values.
        Parameters:
        image - Input image CV_8UC1 or CV_8UC3 with a single text line (or word). text elements found (e.g. words). recognition of individual text elements found (e.g. words). for the recognition of individual text elements found (e.g. words).
        min_confidence - automatically generated
        Returns:
        automatically generated
      • run

        public String run​(Mat image,
                          Mat mask,
                          int min_confidence,
                          int component_level)
      • run

        public String run​(Mat image,
                          Mat mask,
                          int min_confidence)
      • create

        public static OCRHMMDecoder create​(OCRHMMDecoder_ClassifierCallback classifier,
                                           String vocabulary,
                                           Mat transition_probabilities_table,
                                           Mat emission_probabilities_table,
                                           int mode)
        Creates an instance of the OCRHMMDecoder class. Initializes HMMDecoder.
        Parameters:
        classifier - The character classifier with built in feature extractor.
        vocabulary - The language vocabulary (chars when ascii english text). vocabulary.size() must be equal to the number of classes of the classifier.
        transition_probabilities_table - Table with transition probabilities between character pairs. cols == rows == vocabulary.size().
        emission_probabilities_table - Table with observation emission probabilities. cols == rows == vocabulary.size().
        mode - HMM Decoding algorithm. Only OCR_DECODER_VITERBI is available for the moment (<http://en.wikipedia.org/wiki/Viterbi_algorithm>).
        Returns:
        automatically generated
      • create

        public static OCRHMMDecoder create​(OCRHMMDecoder_ClassifierCallback classifier,
                                           String vocabulary,
                                           Mat transition_probabilities_table,
                                           Mat emission_probabilities_table)
        Creates an instance of the OCRHMMDecoder class. Initializes HMMDecoder.
        Parameters:
        classifier - The character classifier with built in feature extractor.
        vocabulary - The language vocabulary (chars when ascii english text). vocabulary.size() must be equal to the number of classes of the classifier.
        transition_probabilities_table - Table with transition probabilities between character pairs. cols == rows == vocabulary.size().
        emission_probabilities_table - Table with observation emission probabilities. cols == rows == vocabulary.size(). (<http://en.wikipedia.org/wiki/Viterbi_algorithm>).
        Returns:
        automatically generated
      • create

        public static OCRHMMDecoder create​(String filename,
                                           String vocabulary,
                                           Mat transition_probabilities_table,
                                           Mat emission_probabilities_table,
                                           int mode,
                                           int classifier)
        Creates an instance of the OCRHMMDecoder class. Loads and initializes HMMDecoder from the specified path
        Parameters:
        filename - automatically generated
        vocabulary - automatically generated
        transition_probabilities_table - automatically generated
        emission_probabilities_table - automatically generated
        mode - automatically generated
        classifier - automatically generated
        Returns:
        automatically generated
      • create

        public static OCRHMMDecoder create​(String filename,
                                           String vocabulary,
                                           Mat transition_probabilities_table,
                                           Mat emission_probabilities_table,
                                           int mode)
        Creates an instance of the OCRHMMDecoder class. Loads and initializes HMMDecoder from the specified path
        Parameters:
        filename - automatically generated
        vocabulary - automatically generated
        transition_probabilities_table - automatically generated
        emission_probabilities_table - automatically generated
        mode - automatically generated
        Returns:
        automatically generated
      • create

        public static OCRHMMDecoder create​(String filename,
                                           String vocabulary,
                                           Mat transition_probabilities_table,
                                           Mat emission_probabilities_table)
        Creates an instance of the OCRHMMDecoder class. Loads and initializes HMMDecoder from the specified path
        Parameters:
        filename - automatically generated
        vocabulary - automatically generated
        transition_probabilities_table - automatically generated
        emission_probabilities_table - automatically generated
        Returns:
        automatically generated