Page Frame Detection for Marginal Noise Removal from Scanned Documents
Identifieur interne : 000E30 ( Main/Merge ); précédent : 000E29; suivant : 000E31Page Frame Detection for Marginal Noise Removal from Scanned Documents
Auteurs : Faisal Shafait [Allemagne] ; Joost Van Beusekom [Allemagne] ; Daniel Keysers [Allemagne] ; M. Breuel [Allemagne]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2007.
Abstract
Abstract: We describe and evaluate a method to robustly detect the page frame in document images, locating the actual page contents area and removing textual and non-textual noise along the page borders. We use a geometric matching algorithm to find the optimal page frame, which has the advantages of not assuming the existence of whitespace between noisy borders and actual page contents, and of giving a practical solution to the page frame detection problem without the need for parameter tuning. We define suitable performance measures and evaluate the algorithm on the UW-III database. The results show that the error rates are below 4% for each of the performance measures used. In addition, we demonstrate that the use of page frame detection reduces the optical character recognition (OCR) error rate by removing textual noise. Experiments using a commercial OCR system show that the error rate due to elements outside the page frame is reduced from 4.3% to 1.7% on the UW-III dataset.
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DOI: 10.1007/978-3-540-73040-8_66
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Breuel</name><affiliation wicri:level="4"><country xml:lang="fr">Allemagne</country><wicri:regionArea>Department of Computer Science, Technical University of Kaiserslautern, D-67663 Kaiserslautern</wicri:regionArea><placeName><region type="land" nuts="2">Rhénanie-Palatinat</region><settlement type="city">Kaiserslautern</settlement></placeName><orgName type="university">Université de technologie de Kaiserslautern</orgName></affiliation><affiliation wicri:level="1"><country wicri:rule="url">Allemagne</country></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2007</date></imprint><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series><idno type="istex">64EFFD5C6F7619CFA2A5269C1C633E03166E1D88</idno><idno type="DOI">10.1007/978-3-540-73040-8_66</idno><idno type="ChapterID">66</idno><idno type="ChapterID">Chap66</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: We describe and evaluate a method to robustly detect the page frame in document images, locating the actual page contents area and removing textual and non-textual noise along the page borders. We use a geometric matching algorithm to find the optimal page frame, which has the advantages of not assuming the existence of whitespace between noisy borders and actual page contents, and of giving a practical solution to the page frame detection problem without the need for parameter tuning. We define suitable performance measures and evaluate the algorithm on the UW-III database. The results show that the error rates are below 4% for each of the performance measures used. In addition, we demonstrate that the use of page frame detection reduces the optical character recognition (OCR) error rate by removing textual noise. Experiments using a commercial OCR system show that the error rate due to elements outside the page frame is reduced from 4.3% to 1.7% on the UW-III dataset.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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