Ancient documents bleed-through evaluation and its application for predicting OCR error rates
Identifieur interne : 000575 ( Main/Exploration ); précédent : 000574; suivant : 000576Ancient documents bleed-through evaluation and its application for predicting OCR error rates
Auteurs : V. Rabeux [France] ; N. Journet [France] ; J. P. Domenger [France]Source :
- Proceedings of SPIE, the International Society for Optical Engineering [ 0277-786X ] ; 2011.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Méthode statistique.
English descriptors
- KwdEn :
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.
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Le document en format XML
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Journet</name><affiliation wicri:level="4"><inist:fA14 i1="01"><s1>LaBRI, Universite de Bordeaux, 351, cours de la Liberation</s1><s2>Talence</s2><s3>FRA</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>France</country><placeName><settlement type="city">Talence</settlement><settlement type="city" wicri:auto="agglo">Bordeaux</settlement></placeName><orgName type="university">Université de Bordeaux</orgName><placeName><settlement type="city">Bordeaux</settlement><region type="region" nuts="2">Aquitaine</region></placeName></affiliation></author><author><name sortKey="Domenger, J P" sort="Domenger, J P" uniqKey="Domenger J" first="J. P" last="Domenger">J. P. Domenger</name><affiliation wicri:level="4"><inist:fA14 i1="01"><s1>LaBRI, Universite de Bordeaux, 351, cours de la Liberation</s1><s2>Talence</s2><s3>FRA</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>France</country><placeName><settlement type="city">Talence</settlement><settlement type="city" wicri:auto="agglo">Bordeaux</settlement></placeName><orgName type="university">Université de Bordeaux</orgName><placeName><settlement type="city">Bordeaux</settlement><region type="region" nuts="2">Aquitaine</region></placeName></affiliation></author></analytic><series><title level="j" type="main">Proceedings of SPIE, the International Society for Optical Engineering</title><title level="j" type="abbreviated">Proc. SPIE Int. Soc. Opt. 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Eng.</title><idno type="ISSN">0277-786X</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Document image processing</term><term>Error rate</term><term>Feasibility</term><term>Imagery</term><term>Inks</term><term>Old document</term><term>Optical character recognition</term><term>Statistical method</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Imagerie</term><term>Encre</term><term>Reconnaissance optique caractère</term><term>Taux erreur</term><term>Document ancien</term><term>Traitement image document</term><term>Méthode statistique</term><term>Faisabilité</term><term>0130C</term><term>4230</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Méthode statistique</term></keywords></textClass></profileDesc></teiHeader><front><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 <sup>*</sup> 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></front></TEI><affiliations><list><country><li>France</li></country><region><li>Aquitaine</li></region><settlement><li>Bordeaux</li><li>Talence</li></settlement><orgName><li>Université de Bordeaux</li></orgName></list><tree><country name="France"><noRegion><name sortKey="Rabeux, V" sort="Rabeux, V" uniqKey="Rabeux V" first="V." last="Rabeux">V. 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