Publication:
OCR Error Correction for Unconstrained Vietnamese Handwritten Text
OCR Error Correction for Unconstrained Vietnamese Handwritten Text
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Date
2019
Authors
Quoc-Dung Nguyen
Duc-Anh Le
Ivan Zelinka
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Abstract
Post-processing is an essential step in detecting and correcting errors in OCR-generated texts. In this paper, we present an automatic OCR post-processing model which comprises both error detection and error correction phases for OCR output texts of unconstrained Vietnamese handwriting. We propose a hybrid approach of generating and scoring correction candidates for both non-syllable and real-syllable errors based on the linguistic features as well as the error characteristics of OCR outputs. We evaluate our proposed model on a Vietnamese benchmark database at the line level. The experimental results show that our model achieves 4.17% of character error rate (CER) and 9.82% of word error rate (WER), which helps improve both CER and WER of an attention-based encoder-decoder approach by 0.5% and 3.5% respectively on the VNOnDB-Line dataset of the Vietnamese online handwritten text recognition competition (VOHTR2018). These results outperform those obtained by various recognition systems in the VOHTR2018 competition.
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Keywords
Unconstrained Vietnamese handwriting,
OCR,
Post-processing,
Error detection,
Error correction