Back to Search Start Over

Improved visual saliency estimation on manufactured surfaces using high-dynamic reflectance transformation imaging

Authors :
Alamin Mansouri
Marvin Nurit
Hermine Chatoux
S. Maniglier
Pierre Jochum
Gaëtan Le Goïc
Equipe CORES [ImViA - EA7535] (CORES)
Imagerie et Vision Artificielle [Dijon] (ImViA)
Université de Bourgogne (UB)-Université de Bourgogne (UB)
CEntre Technique des Industries Mécaniques (CETIM)
CEntre Technique des Industries Mécaniques - Cetim (FRANCE)
CETEHOR [Département technique du Comité FRANCECLAT]
Comité Francéclat
ANR-17-CE10-0005,NAPS,Mesure, Modélisation et Pilotage de l'APparence des états de SUrfaces tridimensionnels(2017)
Source :
Fifteenth International Conference on Quality Control by Artificial Vision, Fifteenth International Conference on Quality Control by Artificial Vision, May 2021, Tokushima, Japan. pp.51, ⟨10.1117/12.2589748⟩
Publication Year :
2021
Publisher :
HAL CCSD, 2021.

Abstract

International audience; Reflectance Transformation Imaging (RTI) is a technique for estimating the surface local angular reflectance and characterizing the visual properties by varying lighting directions and capturing a set of stereo-photometric images. The proposed method, namely HD-RTI, is based on the coupling of RTI and HDR imaging techniques. The HD-RTI automatically optimizes the necessary exposure times for each angle of illumination by using the response of the scene. Our method is applied to industrial surfaces with micro-scratches from which we will estimate saliency information. Results show that coupling HDR and RTI enhance the characterization and therefore the discrimination on the surfaces visual saliency maps. It leads to an increase in robustness for visual quality assessment tasks.

Details

Language :
English
Database :
OpenAIRE
Journal :
Fifteenth International Conference on Quality Control by Artificial Vision, Fifteenth International Conference on Quality Control by Artificial Vision, May 2021, Tokushima, Japan. pp.51, ⟨10.1117/12.2589748⟩
Accession number :
edsair.doi.dedup.....a184ac0baea6442017a63782e789456a
Full Text :
https://doi.org/10.1117/12.2589748⟩