Year: 2024
Type: conference-paper
Abstract: This paper presents a method for the automatic extraction of the structure of wastewater networks from geographical maps, as well as their representation in the form of graphs. The approach consists first in detecting the different important elementary elements composing a wastewater network, such as the manholes, their identifiers (using optical character recognition, OCR), and the wastewater pipes that connect them. Detecting these elementary elements is a first difficult problem, despite many existing tools, mainly due to the quality of the wastewater network maps used. However, the challenge addressed in this paper is how to select the relevant elementary elements detected, and bring them together to finally extract the wastewater network. One of the main contributions of this paper is to propose an efficient algorithm to solve these selection and assignment problems (e.g., manhole identifiers to manholes represented by circles). We also deal with the situation of isolated nodes to have the most connected clusters possible. The experimental results conducted on real map data show very promising results despite the low quality of the maps.
Institutions: Sidi Mohamed Ben Abdellah University, Centre National de la Recherche Scientifique, Centre de Recherche en Informatique de Lens, Université d'Artois, Université de Montpellier, Laboratoire HydroSciences Montpellier, Institut de Recherche pour le Développement, Institut national de recherche en sciences et technologies du numérique, Aix-Marseille Université, Institut Universitaire des Systèmes Thermiques Industriels, LEMON: Littoral, Environnement, Modèles et Outils Numériques
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4405707377