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An In-depth Analysis of OCR Errors for Unconstrained Vietnamese Handwriting

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F20%3A10247263" target="_blank" >RIV/61989100:27240/20:10247263 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27740/20:10247263

  • Result on the web

    <a href="https://link.springer.com/content/pdf/10.1007%2F978-3-030-63924-2_26.pdf" target="_blank" >https://link.springer.com/content/pdf/10.1007%2F978-3-030-63924-2_26.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-63924-2_26" target="_blank" >10.1007/978-3-030-63924-2_26</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    An In-depth Analysis of OCR Errors for Unconstrained Vietnamese Handwriting

  • Original language description

    OCR post-processing is an essential step to improve the accuracy of OCR-generated texts by detecting and correcting OCR errors. In this paper, the OCR texts are resulted from an OCR engine which is based on the attention-based encoder-decoder model for unconstrained Vietnamese handwriting. We identify various kinds of Vietnamese OCR errors and their possible causes. Detailed statistics of Vietnamese OCR errors are provided and analyzed at both character level and syllable level, using typical OCR error characteristics such as error rate, error mapping/edit, frequency and error length. Furthermore, the statistical analyses are done on training and test sets of a benchmark database to infer whether the test set is the appropriate representative of the training set regarding the OCR error characteristics. We also discuss the choice of designing OCR post-processing approaches at character level or at syllable level relying on provided statistics of studied datasets. (C) 2020, Springer Nature Switzerland AG.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10200 - Computer and information sciences

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Volume 12466

  • ISBN

    978-3-030-63923-5

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    14

  • Pages from-to

    448-461

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Quy Nhon

  • Event date

    Nov 25, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article