Open Source Tesseract in Re-OCR of Finnish Fraktur from 19th and Early 20th Century Newspapers and Journals – Collected Notes on Quality Improvement

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Creating and Using Ground Truth OCR Sample Data for Finnish Historical Newspapers and Journals

The National Library of Finland (NLF) has digitized historical newspapers, journals and ephemera published in Finland since the late 1990s. The present collection consists of about 12.9 million pages mainly in Finnish and Swedish. Out of these about 7.36 million pages are freely available on the web site digi.kansalliskirjasto.fi. The copyright restricted part of the collection can be used at six legal deposit libraries in different parts of Finland. The time period of the open collection is from 1771 to 1929. The years 1920–1929 were opened in January 2018. This paper presents the ground truth Optical Character Recognition data of about 500 000 Finnish words that has been compiled at the NLF for development of a new OCR process for the collection. We discuss compilation of the data and show basic results of the new OCR process in comparison to current OCR using the ground truth data.Peer reviewe

Research and Development Efforts on the Digitized Historical Newspaper and Journal Collection of The National Library of Finland

The National Library of Finland (NLF) has digitized historical newspapers, journals and ephemera published in Finland since the late 1990s. The present collection consists of about 12.8 million pages mainly in Finnish and Swedish. Out of these about 7.36 million pages are freely available on the web site digi.kansalliskirjasto.fi (Digi). The copyright restricted part of the collection can be used at six legal deposit libraries in different parts of Finland. The time period of the open collection is from 1771 to 1929. This paper presents work that has been carried out in the NLF related to the historical newspaper and journal collection. We offer an overall account of research and development related to the data.Peer reviewe

Improving Optical Character Recognition of Finnish Historical Newspapers with a Combination of Fraktur & Antiqua Models and Image Preprocessing

In this paper we describe a method for improving the optical character recognition (OCR) toolkit Tesseract for Finnish historical documents. First we create a model for Finnish Fraktur fonts. Second we test Tesseract with the created Fraktur model and Antiqua model on single images and combinations of images with different image preprocessing methods. Against commercial ABBYY FineReader toolkit our method achieves 27.48% (FineReader 7 or 8) and 9.16% (FineReader 11) improvement on word level. Keywords: Optical Character Recognition, OCR Quality, Digital Image Processing, Binarization, Noise Removal, Tesseract, Finnish, Historical DocumentsPeer reviewe