OCRticle - a Structure-Aware OCR Application

Authors Sofia G. Rodrigues dos Santos , J. João Dias de Almeida

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Author Details

Sofia G. Rodrigues dos Santos
  • Informatics Department, University of Minho, Braga, Portugal
J. João Dias de Almeida
  • ALGORITMI/LASI, University of Minho, Braga, Portugal

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Sofia G. Rodrigues dos Santos and J. João Dias de Almeida. OCRticle - a Structure-Aware OCR Application. In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 8:1-8:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


While there are currently many applications and websites capable of performing Optical Character Recognition (OCR), none of the widely available options offer structured OCR, i.e., OCR that maintains the text’s original structure. For example, if a document has a title, after performing OCR on it, the title should have a different formatting, in order to distinguish it from the rest of the text. This paper covers the topic of structure-aware OCR, first by describing the current state of OCR tools, then by showcasing a prototype tool capable of retaining the structure of articles scanned from an image.

Subject Classification

ACM Subject Classification
  • Applied computing → Optical character recognition
  • OCR
  • Optical Character Recognition
  • Data Structure
  • Data Parsing
  • Document Structure


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