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  4. Recognizing and Sequencing Multi-word Texts in Maps Using an Attentive Pointer
 
preprint

Recognizing and Sequencing Multi-word Texts in Maps Using an Attentive Pointer

Zou, Mengjie  
•
Dai, Tianhao  
•
Petitpierre, Rémi  
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April 15, 2025

Extracting and recognizing texts from historical maps presents significant challenges due to complex layouts, varied typographic conventions, and the entanglement of multiple sequences. In this paper, we present a modular neural framework for linking and ordering text segments together. This task goes beyond simple word recognition; it enables to recover the complete text sequences. Our solution, based on an Attentive Pointer, successfully manages the presence of distractor words. It leverages both positional and Bézier directional features. We demonstrate the effectiveness of our framework with two practical applications. First, we prove its scalability by applying it to the 1890s Ordnance Survey of London, retrieving 285,846 text sequences. Second, we validate the practical effectiveness of the sequenced placenames by geocoding them and showcasing their capability to automate city maps realignment. Our approach is scalable, trainable, and generic. It supports hierarchical integration and multimodal feature fusion by design, making it an extensible and modular framework for further advancements.

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Type
preprint
DOI
10.21203/rs.3.rs-6330456/v1
Author(s)
Zou, Mengjie  

École Polytechnique Fédérale de Lausanne

Dai, Tianhao  

École Polytechnique Fédérale de Lausanne

Petitpierre, Rémi  

École Polytechnique Fédérale de Lausanne

Vaienti, Beatrice  

École Polytechnique Fédérale de Lausanne

Kaplan, Frédéric  

École Polytechnique Fédérale de Lausanne

Lenardo, Isabella di  orcid-logo

École Polytechnique Fédérale de Lausanne

Date Issued

2025-04-15

Publisher

Research Square Platform LLC

Subjects

Multi-word linking

•

Text detection

•

Placenames recognition

•

Map processing

Written at

EPFL

EPFL units
DLAB  
DHI-GE  
DHLAB  
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Available on Infoscience
May 7, 2025
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/249929
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