DocumentCode
2146962
Title
Character Enhancement for Historical Newspapers Printed Using Hot Metal Typesetting
Author
Konya, Iuliu ; Eickeler, Stefan ; Seibert, Christoph
Author_Institution
Fraunhofer IAIS, St. Augustin, Germany
fYear
2011
fDate
18-21 Sept. 2011
Firstpage
936
Lastpage
940
Abstract
We propose a new method for an effective removal of the printing artifacts occurring in historical newspapers which are caused by problems in the hot metal typesetting, a widely used printing technique in the late 19th and early 20th century. Such artifacts typically appear as thin lines between single characters or glyphs and are in most cases connected to one of the neighboring characters. The quality of the optical character recognition (OCR) is heavily influenced by this type of printing artifacts. The proposed method is based on the detection of (near) vertical segments by means of directional single-connected chains (DSCC). In order to allow the robust processing of complex decorative fonts such as Fraktur, a set of rules is introduced. This allows us to successfully process prints exhibiting artifacts with a stroke width even higher than that of most thin characters stems. We evaluate our approach on a dataset consisting of old newspaper excerpts printed using Fraktur fonts. The recognition results on the enhanced images using two independent OCR engines (ABBYY Fine Reader and Tesseract) show significant improvements over the originals.
Keywords
image enhancement; optical character recognition; printing industry; publishing; ABBYY FineReader; Fraktur fonts; Tesseract; character enhancement; complex decorative fonts; directional single connected chains; enhanced images; historical newspapers; hot metal typesetting; optical character recognition; printing artifacts removal; printing technique; Algorithm design and analysis; Engines; Metals; Optical character recognition software; Printing; Text analysis; Typesetting; OCR; character enhancement; historical documents; hot metal typesetting; retro-digitization;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location
Beijing
ISSN
1520-5363
Print_ISBN
978-1-4577-1350-7
Electronic_ISBN
1520-5363
Type
conf
DOI
10.1109/ICDAR.2011.190
Filename
6065448
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