OCR Error Correction for Vietnamese OCR Text with Different Edit Distances

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F22%3A10252180" target="_blank" >RIV/61989100:27240/22:10252180 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-031-14627-5_13" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-14627-5_13</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-14627-5_13" target="_blank" >10.1007/978-3-031-14627-5_13</a>

Jazyk výsledku

angličtina

Název v původním jazyce

OCR Error Correction for Vietnamese OCR Text with Different Edit Distances

Popis výsledku v původním jazyce

Candidate word generation by character edit operations is an important method that has been employed in many OCR error correction approaches. In this paper, we study how character edit distances impact the performance of OCR error correction. We propose the algorithm of generating correction candidates with different edit distances. Correction candidates for both non-word and real-word errors are considered. The candidates are scored and ranked based on linguistic features and edit probability. The experiments are tested on the VNOnDB database used in the Vietnamese online handwritten text recognition competition (VOHTR 2018). We evaluate the error correction performance on different edit distances in terms of two error metrics, character error rate (CER) and word error rate (WER). It is shown that the edit distances of 1 and 2 obtain better correction results instead of higher edit distances. (C) 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Název v anglickém jazyce

OCR Error Correction for Vietnamese OCR Text with Different Edit Distances

Popis výsledku anglicky

Candidate word generation by character edit operations is an important method that has been employed in many OCR error correction approaches. In this paper, we study how character edit distances impact the performance of OCR error correction. We propose the algorithm of generating correction candidates with different edit distances. Correction candidates for both non-word and real-word errors are considered. The candidates are scored and ranked based on linguistic features and edit probability. The experiments are tested on the VNOnDB database used in the Vietnamese online handwritten text recognition competition (VOHTR 2018). We evaluate the error correction performance on different edit distances in terms of two error metrics, character error rate (CER) and word error rate (WER). It is shown that the edit distances of 1 and 2 obtain better correction results instead of higher edit distances. (C) 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10200 - Computer and information sciences

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název statě ve sborníku

Lecture Notes in Networks and Systems. Volume 527

ISBN

978-3-031-14626-8

ISSN

2367-3370

e-ISSN

2367-3389

Počet stran výsledku

10

Strana od-do

130-139

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Sanda

Datum konání akce

7. 9. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000870692600013