Premium
Using Appearance Maps drawn from goniocolorimetric profiles to predict sensory appreciation of red and blue paints
Author(s) -
Eterradossi Olivier,
Perquis Stéphane,
Mikec Véronique
Publication year - 2009
Publication title -
color research and application
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.393
H-Index - 62
eISSN - 1520-6378
pISSN - 0361-2317
DOI - 10.1002/col.20463
Subject(s) - multidimensional scaling , sensory system , perception , mathematics , artificial intelligence , stimulus (psychology) , sensory analysis , scaling , pattern recognition (psychology) , computer science , psychology , cognitive psychology , statistics , geometry , neuroscience
In this article, we test the ability of a sensorialy calibrated version of Appearance Maps, a recently suggested tool based on Multidimensional Scaling and Procrustes Analysis, to understand and predict the sensory evaluation of automotive paints by trained subjects. This tool has been applied to a set of 13 industrial samples representing three shades: two effect shades, both at 4 levels of quality, and one solid shade at 5 levels of quality, which were evaluated for their overall appearance relative to the distinctness of image and the “Orange Peel” effect. The results of descriptive analysis performed on the samples by a panel of 15 trained panelists (paint experts and sensory assessors) are compared with information taken from the maps. One of the Appearance Map coordinates is shown to correlate well with mean sensory evaluations. Different relations (either sigmoid curves or power laws) between map coordinate considered as a stimulus and sensory scores taken as perception are found for the different shades, and comments on possible similarities between the observed relations and known models are made. © 2008 Wiley Periodicals, Inc. Col Res Appl, 34, 68–74, 2009.