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Evaluation of performance of various color‐difference formulae using an experimental black dataset
Author(s) -
Shamey Renzo,
Lin Juan,
Sawatwarakul Weethima,
Cao Renbo
Publication year - 2014
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.21844
Subject(s) - hue , mathematics , color difference , lightness , statistics , color space , artificial intelligence , significant difference , correlation coefficient , computer science , enhanced data rates for gsm evolution , image (mathematics)
The objective of this study was to develop a specific visual dataset comprising black‐appearing samples with low lightness ( L* ranging from approximately 10.4 to 19.5), varying in hue and chroma, evaluating their visual differences against a reference sample, and testing the performance of major color difference formulas currently in use as well as OSA‐UCS‐based models and more recent CAM02 color difference formulas including CAM02‐SCD and CAM02‐UCS models. The dataset comprised 50 dyed black fabric samples of similar structure, and a standard ( L *= 15.33, a * = 0.14, b * = −0.82), with a distribution of small color differences, in ΔE * ab , from 0 to approximately 5. The visual color difference between each sample and the standard was assessed by 19 observers in three separate sittings with an interval of at least 24 hours between trials using an AATCC standard gray scale for color change, and a total of 2850 assessments were obtained. A third‐degree polynomial equation was used to convert gray scale ratings to visual differences. The Standard Residual Sum of Squares index (STRESS) and Pearson's correlation coefficient ( r ), were used to evaluate the performance of various color difference formulae based on visual results. According to the analysis of STRESS index and correlation coefficient results CAM02 color difference equations exhibited the best agreement against visual data with statistically significant improvement over other models tested. The CIEDE2000 (1:1:1) equation also showed good performance in this region of the color space. © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 589–598, 2014