Beschreibung:
<jats:p>Iterating with new and improved OCR solutions enforces decision making when
it comes to targeting the right candidates for reprocessing. This especially
applies when the underlying data collection is of considerable size and rather
diverse in terms of fonts, languages, periods of publication and consequently
OCR quality. This article captures the efforts of the National Library of
Luxembourg to support those targeting decisions. They are crucial in order to
guarantee low computational overhead and reduced quality degradation risks,
combined with a more quantifiable OCR improvement. In particular, this work
explains the methodology of the library with respect to text block level
quality assessment. Through extension of this technique, a regression model,
that is able to take into account the enhancement potential of a new OCR
engine, is also presented. They both mark promising approaches, especially for
cultural institutions dealing with historical data of lower quality.</jats:p>