Open AccessA method to improve the color rendering accuracy in cultural heritage: preliminary results
Author(s) -
Dario Allegra,
Giuseppe Furnari,
S Gargano,
Anna Maria Gueli,
Stefania Claudia Parisi,
Stefania Pasquale,
Filippo Stanco,
Giuseppe Stella
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2204/1/012057
Subject(s) - cultural heritage , rgb color model , rendering (computer graphics) , computer science , computer vision , color space , artificial intelligence , metadata , color balance , color correction , icc profile , color rendering index , computer graphics (images) , color model , color image , geography , image processing , engineering , image (mathematics) , archaeology , electrical engineering , light emitting diode , operating system
Color specification is an important challenge in many application domains including Cultural Heritage. The collection of metadata concerning Cultural Heritage involves the valorization, fruition and becomes part of the conservation process. It becomes essential to find methods that simplify and optimize the acquisition of such data as color information. In this regard, in this work we present the preliminary results of a project that involves the acquisition by 3D scanner of samples of different colors placed in a controlled environment and with different illumination conditions. To make more accurate the color rendering, the color coordinates of each sample were measured by a spectrophotometer. All the obtained measurements become part of a dataset with which to train a machine learning model that learns how to perform the transformation from the RGB to the CIELab color space in different lighting condition.