This repository provides access to the scripts utilized during the research titled "Quality-aware Human-Machine Text Extraction for Biocollections using Ensembles of OCRs".
The automated steps of the text extraction process are the following (in order)
-
Lines' Extraction
1.1. Resize the images that are bigger than 10MB (Google Cloud limitations). Manually use script resizeDir_mt.py.
1.2. Line segmentation from the Google Cloud Vision API. Script get_lines_google.py. This process also extracts the text from the lines.
1.3. Binarization of the lines with OCRopus. Script binarizeDir_mt.py.
1.4. Extraction of the lines' text using OCRopus. Script recognizeDir_mt.py.
1.5. Extraction of the lines' text using Tesseract. Script tessDir_mt.py. -
Ensemble of OCRs
2.1. Accept line through majority voting. Script getLinesAccepted.py.
2.2. Separate the lines with match for the 3 OCR engines. Script getLinesAccepted_Match3.py.
2.3. N-grams construction. Script get_n_grams.py.
2.4. Computation of the per-character descriptive statistics. Script get_stats_from_probs.py.
2.5. Augment the probabilities of the characters in the lines using the n-grams and descriptive statistics. Script augment_prob_ngrams.py.
2.6. Accept the lines with all their characters with probability 1.0. Script accept_from_ngrams.py -
Compose the Full Transcription Text of the Images.
3.1. Construction of the full text transcriptions from the lines. Script build_labels.py.
3.2. Computation of the Damerau-Levenshtein similarity to the ground truth data. Script fulltext_similarity_DL_dir.py.
For a more detailed description of the text extraction process, review the following Jupyter Notebooks:
1. Lines' Extraction: [L_aocr_entomology.ipynb](https://github.com/acislab/HuMaIN_Text_Extraction/blob/master/notebooks/L_aocr_entomology.ipynb).
2. Ensemble of OCRs: [E_aocr_entomology.ipynb](https://github.com/acislab/HuMaIN_Text_Extraction/blob/master/notebooks/E_aocr_entomology.ipynb).
Copyright 2019 Advanced Computing and Information Systems (ACIS) Lab - UF (https://www.acis.ufl.edu)
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