AIKON: a modular computer vision platform for historical corpora

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Authors: Ségolène Albouy, Somkeo Norindr, Paul Kervegan, Fouad Aouinti, Rémy Delanaux, Clara Grometto, Robin Champenois, Stavros Lazaris, Alexandre Guilbaud, Matthieu Husson, Mathieu Aubry
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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Abstract Historical document analysis has progressed to a point where the main bottleneck for many historical applications is not algorithms, but relevant interfaces, that can support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 aikon implements a complete workflow for historical document analysis, from corpus constitution to ai outputs validation and interpretation.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.

Fields of Study & Subjects

Handwritten Text Recognition Techniques Image Processing and 3D Reconstruction Natural Language Processing Techniques

Publication details

Journal / source
International Journal on Document Analysis and Recognition (IJDAR)
Publication date
30 June 2026
Language
EN