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Ancient documents bleed-through evaluation and its application for predicting OCR error rates

Identifieur interne : 000353 ( Main/Exploration ); précédent : 000352; suivant : 000354

Ancient documents bleed-through evaluation and its application for predicting OCR error rates

Auteurs : Vincent Rabeux [France] ; Nicholas Journet [France] ; Jean-Philippe Domenger [France]

Source :

RBID : Hal:hal-00570247

Abstract

This article presents a way to evaluate the bleed-through defect on very old document images. We design measures to quantify and evaluate the verso ink bleeding through the paper onto the recto side. Measuring the bleed-through defect alows us to perform statistical analysis that are able to predict the feasibility of different post-scan tasks. In this article we choose to illustrate our measures by creating two OCR error rate predicting models based bleed-through evaluation. Two models are proposed, one for Abbyy FineReader ∗ which is a very power-full commercial OCR and OCRopus † which is sponsored by Google. Both prediction models appears to be very accurate when calculating various statistic indicators.

Url:


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<div type="abstract" xml:lang="en">This article presents a way to evaluate the bleed-through defect on very old document images. We design measures to quantify and evaluate the verso ink bleeding through the paper onto the recto side. Measuring the bleed-through defect alows us to perform statistical analysis that are able to predict the feasibility of different post-scan tasks. In this article we choose to illustrate our measures by creating two OCR error rate predicting models based bleed-through evaluation. Two models are proposed, one for Abbyy FineReader ∗ which is a very power-full commercial OCR and OCRopus † which is sponsored by Google. Both prediction models appears to be very accurate when calculating various statistic indicators.</div>
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