Automatic Calculation of Damage Rate of Roofs Based on Image Segmentation - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2022

Automatic Calculation of Damage Rate of Roofs Based on Image Segmentation

Shono Fujita
  • Fonction : Auteur
  • PersonId : 1250497
Michinori Hatayama
  • Fonction : Auteur
  • PersonId : 1250493

Résumé

In the event of a natural disaster, Japanese local governments investigate the level of damage of the buildings and issue damage certificates to the victims. The damage certificate is used to determine the contents of support provided to the victims; hence, they must be issued rapidly and accurately. However, in the past, the investigation of damage was time consuming, thus delaying the support provided to the victims. Additionally, while investigating the roof of the damaged building, it was difficult for the investigators to look at the entire roof and calculate the damage rate accurately. To address this issue, we have developed an image processing model to automatically calculate the rate of damage on a roof through image recognition from aerial photos. To circumvent the problem of lack of training data reported in our previous study [1], in this study, roof images were divided into roof surfaces based on image segmentation by deep learning, and the number of training data was increased. Our model calculated the rate of damage for up to 80% of roof data more accurately than the conventional assessment by a field investigator.
Fichier sous embargo
Fichier sous embargo
0 7 15
Année Mois Jours
Avant la publication
mercredi 1 janvier 2025
Fichier sous embargo
mercredi 1 janvier 2025
Connectez-vous pour demander l'accès au fichier

Dates et versions

hal-04082628 , version 1 (26-04-2023)

Licence

Paternité

Identifiants

Citer

Shono Fujita, Michinori Hatayama. Automatic Calculation of Damage Rate of Roofs Based on Image Segmentation. 6th International Conference on Information Technology in Disaster Risk Reduction (ITDRR), Oct 2021, Morioka, Japan. pp.3-22, ⟨10.1007/978-3-031-04170-9_1⟩. ⟨hal-04082628⟩
23 Consultations
1 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More