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Automatic Text Recognition (ATR) - Step 4: Layout Analysis

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Learning Outcome

After completing this resource, learners will be able to:

  • Distinguish between different methods of layout analysis including zoning and segmentation.
  • Utilise software tools to perform optical layout analysis effectively.
  • Analyse the structural elements of a document to facilitate accurate text extraction.
  • Configure ATR systems to recognise and process various document layouts.

You can read the blogpost (available in English, French, and German), and watch our video (with subtitles in English, French, and German) embedded in the post.

Interested in learning more?

Check out "Automatic Text Recognition - Step 4: Layout Analysis"

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Cite as

Alix Chagué and Hugo Scheithauer (2024). Automatic Text Recognition (ATR) - Step 4: Layout Analysis. Version 1.0.0. Edited by Anne Baillot and Mareike König. Deutsches Historisches Institut Paris. [Training module]. https://harmoniseatr.hypotheses.org/1215

Reuse conditions

Resources hosted on DARIAH-Campus are subjects to the DARIAH-Campus Training Materials Reuse Charter

Full metadata

Title:
Automatic Text Recognition (ATR) - Step 4: Layout Analysis
Authors:
Alix Chagué, Hugo Scheithauer
Domain:
Social Sciences and Humanities
Language:
en
Published:
5/10/2024
Content type:
Training module
Licence:
CCBY 4.0
Sources:
DARIAH
Topics:
Editing tools, Machine Learning, Automatic Text Recognition
Version:
1.0.0