Automatic Text Recognition Made Easy
Explore this curriculum on Automatic Text Recognition (ATR) and learn how to efficiently extract full text from heritage material images. Perfectly tailored for researchers, librarians, and archivists, these resources not only enhance your archival research and preservation efforts but also unlock the potential for computational analysis of your sources.
This curriculum is also available in French or German. The production of this curriculum was financed by the DARIAH-ERIC Thematic Funding Scheme 2022.
Resources
Automatic Text Recognition (ATR) - Getting Started
ENKick off your journey into Automatic Text Recognition (ATR) with our introductory tutorial video. This is the first video of a tutorial series dedicated to extracting full text from scanned images.Automatic Text Recognition (ATR) - Where and How to Get Images
ENThis tutorial explores where and how to find, create, and collect images of textual material, a crucial initial step in any process using Automatic Text Recognition (ATR).Automatic Text Recognition (ATR)- Pre-Processing and Image Optimisation
ENGet ready to improve the quality of your scanned images before moving to the processing phase of your ATR project.Automatic Text Recognition (ATR) - Layout Analysis
ENDiscover the subtleties of region and line segmentation and learn about the purpose of layout analysis for Automatic Text Recognition!Automatic Text Recognition (ATR) - Text Recognition and Post-ATR Correction
ENDive into the fine-tuning of Automatic Text Recognition outputs!Automatic Text Recognition (ATR) - End Formats and Reusability
ENIncrease the visibility of your ATR output while fostering Open Science.