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How Good Is Good Enough? Establishing Quality Thresholds for the Automatic Text Analysis of Retro-Digitized Comics

  • Rita HartelEmail author
  • Alexander Dunst
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11296)

Abstract

Stylometry in the form of simple statistical text analysis has proven to be a powerful tool for text classification, e.g. in the form of authorship attribution. When analyzing retro-digitized comics, manga and graphic novels, the researcher is confronted with the problem that automated text recognition (ATR) still leads to results that have comparatively high error rates, while the manual transcription of texts remains highly time-consuming. In this paper, we present an approach and measures that specify whether stylometry based on unsupervised ATR will produce reliable results for a given dataset of comics images.

Keywords

Graphic novels OCR ATR Automatic text analysis 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Paderborn UniversityPaderbornGermany

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