Open AccessStrip-pair comparison method for building threshold color-difference model: theoretical model validation
Author(s) -
Fernando Brusola,
Ignacio Tortajada,
Ismael Lengua Lengua,
Begoña Jordá,
Guillermo Perís-Fajarnés
Publication year - 2020
Publication title -
optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.395256
Subject(s) - color difference , color space , standard deviation , artificial intelligence , color model , color vision , computer science , ellipsoid , optics , scaling , mathematics , algorithm , statistics , physics , geometry , image (mathematics) , enhanced data rates for gsm evolution , astronomy
This paper presents a method for developing color-difference models near a threshold, based on the serial exploration method described by Torgerson [Theory and Methods of Scaling; Wiley & Sons (1958); Chap. 7], involving the construction of color-control strips of patches arranged in arrays of 2 × n, where n is the number of pairs in the strip. The patches in the lower row should be calorimetrically identical, while the color of the patches in the upper row should vary progressively in constant steps of CIELAB color difference along selected color space vector directions. Prospective observers are instructed to indicate the patch pair number for which they begin to perceive a slight color difference between corresponding patches. The frequency data obtained from the observers was used to build a threshold color-difference model. The intention was to validate the method with theoretical data to determine the effect of the precision with which the strips are constructed, on the accuracy of the estimated parameters. Theoretical frequency data was generated using the CIE94 color difference formula, whose associated color discrimination ellipsoid parameters are very easy to determine, associated with a hypothetical logistic psychometric curve for different color centers. The proposed method allows to determine color discrimination parameters with a precision nearby 4% and an accuracy of 3% with respect to the simulated theoretical parameters, for color samples generated with a standard deviation of Δ E a b ∗=0.2 of the superimposed error around the ideal color difference of pairs of patches.