Acceptability-based Brand Color Tolerance, A Case Study

The Pantone R Formula Guide (or Guide), printed using specially-formulated inks on specified substrates, has been used widely by brands to specify brand color aims. While the Guide is silent on brand color tolerance, there are two competing criteria that influence the brand color tolerance, i.e., pe...

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Bibliographic Details
Main Authors: Chung, R.Y (Author), Liu, Y. (Author)
Format: Article
Language:English
Published: Society for Imaging Science and Technology 2022
Subjects:
Online Access:View Fulltext in Publisher
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001 10.2352-J.ImagingSci.Technol.2022.66.3.030509
008 220718s2022 CNT 000 0 und d
020 |a 10623701 (ISSN) 
245 1 0 |a Acceptability-based Brand Color Tolerance, A Case Study 
260 0 |b Society for Imaging Science and Technology  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.2352/J.ImagingSci.Technol.2022.66.3.030509 
520 3 |a The Pantone R Formula Guide (or Guide), printed using specially-formulated inks on specified substrates, has been used widely by brands to specify brand color aims. While the Guide is silent on brand color tolerance, there are two competing criteria that influence the brand color tolerance, i.e., perceptibility and acceptability. Perceptibility-based color tolerance focuses on “Can I see the difference?” and the permissive difference is in the just-noticeable difference (JND) region. Acceptability-based color tolerance, focusing on “Can I accept the outcome?”, requires fit-for-use cases to identify what the just-acceptable difference (JAD) is. Instead of conducting psychometric tests, this research uses the 2019 Pantone R Formula (Coated) Guide, consisting of 2140 CIELAB colors, and data analyses of the “neighboring color difference” to investigate what is the acceptability-based color tolerance. The result shows that the acceptability-based color tolerance (3 1E00) has more margin than the perceptibility-based color tolerance (2 1E00). © Society for Imaging Science and Technology 2022 
650 0 4 |a Application programs 
650 0 4 |a Case-studies 
650 0 4 |a CIELAB color 
650 0 4 |a Color 
650 0 4 |a Color difference 
650 0 4 |a Colorimetry 
650 0 4 |a Just-noticeable difference 
650 0 4 |a Psychometric test 
650 0 4 |a Research use 
700 1 |a Chung, R.Y.  |e author 
700 1 |a Liu, Y.  |e author 
773 |t Journal of Imaging Science and Technology  |x 10623701 (ISSN)  |g 66 3