Tahitian Pearls' Luster Assessment Automation

Gael Mondonneix , Sébastien Chabrier (1, 2, 3) , Jean-Martial Mari , Alban Gabillon , J P Barriot

1 GePaSUD - Géopôle du Pacifique Sud
2 UPF - Université de la Polynésie Française
3 LabEX CORAIL - Laboratoire d'Excellence CORAIL

This paper represents a preliminary work toward a machine learning process which could be used to automatically assess Tahitian pearls' lustre. In particular, it investigates the different aspects of lustre which could be used to design feature vectors for machine learning algorithms.

Mots clés: Pearl; Lustre; Features; Perception

Domaines: Biologie animale

Gael Mondonneix, Sébastien Chabrier, Jean-Martial Mari, Alban Gabillon, J P Barriot. Tahitian Pearls' Luster Assessment Automation. 2017 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), Oct 2017, Washington, United States. pp.1-9, ⟨10.1109/AIPR.2017.8457974⟩. ⟨hal-03132251⟩