French vital records data gathering and analysis through image processing and machine learning algorithms

Vital records are rich of meaningful historical data concerning city as well as countryside inhabitants that can be used, among others, to study former populations and then reveal the social, economic and demographic characteristics of those populations. However, these studies encounter a main diffi...

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Bibliographic Details
Published in:Journal of data mining and digital humanities Vol. 2021
Main Authors: Plateau-Holleville, Cyprien, Bonnot, Enzo, Gechter, Franck, Heyberger, Laurent
Format: Journal Article
Language:English
Published: INRIA 15.07.2021
Nicolas Turenne
Subjects:
[info.info-ai]computer science [cs]/artificial intelligence [cs.ai]
[info.info-cv]computer science [cs]/computer vision and pattern recognition [cs.cv]
[shs.hist]humanities and social sciences/history
Artificial Intelligence
Computer Science
Computer Vision and Pattern Recognition
handwritten text recognition
historical data
History
Humanities and Social Sciences
machine learning
optical character recognition
Optical Character Recognition
Machine Learning
Historical Data
Handwritten Text Recognition
ISSN:2416-5999, 2416-5999
Online Access:Get full text
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Summary:Vital records are rich of meaningful historical data concerning city as well as countryside inhabitants that can be used, among others, to study former populations and then reveal the social, economic and demographic characteristics of those populations. However, these studies encounter a main difficulty for collecting the data needed since most of these records are scanned documents that need a manual transcription step in order to gather all the data and start exploiting it from a historical point of view. This step consequently slows down the historical research and is an obstacle to a better knowledge of the population habits depending on their social conditions. Therefore in this paper, we present a modular and self-sufficient analysis pipeline using state-of-the-art algorithms mostly regardless of the document layout that aims to automate this data extraction process.
ISSN:2416-5999
2416-5999
DOI:10.46298/jdmdh.7327