One step clustering based on a-contrario framework for detection of alterations in historical violins - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2021

One step clustering based on a-contrario framework for detection of alterations in historical violins

Résumé

Preventive conservation is an important practice in Cultural Heritage. The constant monitoring of the state of conservation of an artwork helps us reduce the risk of damage and number of necessary interventions. In this work, we propose a probabilistic approach for the detection of alterations on the surface of historical violins based on an a-contrario framework. Our method is a one step NFA clustering solution which considers grey-level and spatial density information in one background model. The proposed method is robust to noise and avoids parameter tuning and any assumption about the quantity of the worn-out areas. We have used as input UV induced fluorescence (UVIFL) images for considering details not perceivable with visible light. Tests were conducted on image sequences included in the "Violins UVIFL imagery" dataset. Results illustrate the ability of the algorithm to distinguish the worn area from the surrounding regions. Comparisons with state-of-the-art clustering methods show improved overall precision and recall.
Fichier principal
Vignette du fichier
RezaeiICPR20.pdf (1.08 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04454850 , version 1 (13-02-2024)

Identifiants

Citer

Alireza Rezaei, Sylvie Le Hegarat-Mascle, Emanuel Aldea, Piercarlo Dondi, Marco Malagodi. One step clustering based on a-contrario framework for detection of alterations in historical violins. 2020 25th International Conference on Pattern Recognition (ICPR), Jan 2021, Milan, Italy. pp.9348-9355, ⟨10.1109/ICPR48806.2021.9412129⟩. ⟨hal-04454850⟩
4 Consultations
3 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More