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Defining a practical method of ascertaining textile color acceptability
Author(s) -
Steen Daniel,
Dupont Daniel
Publication year - 2002
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.10094
Subject(s) - textile , observer (physics) , sorting , computer science , ellipsoid , sample (material) , selection (genetic algorithm) , industrial engineering , artificial intelligence , mathematics , computer vision , engineering drawing , operations research , algorithm , engineering , materials science , composite material , chemistry , physics , quantum mechanics , astronomy , chromatography
The relations between supplier and customer are today more important than they have ever been. However, conflicts do sometimes arise between them, deriving from differences in the judgment of color matchings. Colorimetry's role is precisely to avoid such conflicts through instrument measurements. A study was made on the pass/fail problems, based on 1,830 measurements and observations made in industrial textile firms, followed by 350 new tests. Human judgments are as liable to errors as instrument measurements, because the surface effects are often misleading for the observer. This study proposes a sorting method that combines the differences deriving from measurements by colorimetric instruments and by visual judgment. The Color Measurement Committee (CMC) equation, widely used in the textile field, has given excellent practical results. The CIE94 equation, which uses the same principle of ellipsoid tolerance, offers a mathematical simplification as well as further information on the sample observation conditions in order to determine color differences. Nevertheless, these two equations are different, and the CIE94 indexes must not be interpreted with the same tolerances as those of the CMC. Pending the CIE recommendations concerning textile samples, new acceptability tolerances should be redetermined for the CIE94. This article presents an innovative way of calculating metameric indexes that, when coupled with acceptability equations, allow the agreement rate between visual judgment and automatic selection to be increased.