AIKON: a modular computer vision platform for historical corpora

Abstract Historical document analysis has progressed to a point where the main bottleneck for many historical applications is not algorithms, but relevant interfaces, that can support historians’ workflow. While specialized tools exist for text processing and image search, we argue the community lacks a versatile collaborative platform enabling historians to analyze their own corpora from a particular perspective. As a step in this direction, we present aikon , a modular web-platform designed to empower historians with computer vision tools. aikon implements a complete workflow for historical document analysis, from corpus constitution to ai outputs validation and interpretation. It provides a comprehensive research environment combining source management tools with automated processing capabilities as well as multi-user validation and visualization interfaces. We showcase the potential of aikon by presenting modules enabling the investigation of graphical content transmission across large and diverse corpora, a problem for which few modern tools exist, and which is of key interest, for example in History of Science.

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Publication Details

Journal
International Journal on Document Analysis and Recognition (IJDAR)
Published
2026-06-30
DOI
https://doi.org/10.1007/s10032-026-00581-x
Primary Topic
Handwritten Text Recognition Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

AIKON: a modular computer vision platform for historical corpora

Alexandre Guilbaud, Fouad Aouinti, Mathieu Aubry, Matthieu Husson et al.
International Journal on Document Analysis and Recognition (IJDAR)
Handwritten Text Recognition Techniques
article

AIKON: a modular computer vision platform for historical corpora

Alexandre Guilbaud, Fouad Aouinti, Mathieu Aubry, Matthieu Husson, Robin Champenois, Stavros Lazaris, Paul Kervegan, Ségolène Albouy, Somkeo Norindr, Rémy Delanaux
article en

Abstract

Abstract Historical document analysis has progressed to a point where the main bottleneck for many historical applications is not algorithms, but relevant interfaces, that can support historians’ workflow. While specialized tools exist for text processing and image search, we argue the community lacks a versatile collaborative platform enabling historians to analyze their own corpora from a particular perspective. As a step in this direction, we present aikon , a modular web-platform designed to empower historians with computer vision tools. aikon implements a complete workflow for historical document analysis, from corpus constitution to ai outputs validation and interpretation. It provides a comprehensive research environment combining source management tools with automated processing capabilities as well as multi-user validation and visualization interfaces. We showcase the potential of aikon by presenting modules enabling the investigation of graphical content transmission across large and diverse corpora, a problem for which few modern tools exist, and which is of key interest, for example in History of Science.

International Journal on Document Analysis and Recognition (IJDAR)
Centre National de la Recherche Scientifique (FR), École nationale des ponts et chaussées (FR), Université Sorbonne Nouvelle (FR), Université Paris Cité (FR), Observatoire de Paris (FR), Institut de Mathématiques de Jussieu-Paris Rive Gauche (FR), Sorbonne Université (FR), Sorbonne Paris Cité (FR), Systèmes de Référence Temps-Espace (FR), Laboratoire d'Informatique Gaspard-Monge (FR), Université Gustave Eiffel (FR), Orient & Méditerranée (FR), Institut catholique de paris (FR)
European Commission, Agence Nationale de la Recherche, HORIZON EUROPE Framework Programme, European Research Council
Openalex Percentile: Top 99%
Handwritten Text Recognition Techniques
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