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Evaluation of Performance of Twelve Color-Difference Formulae Using Two NCSU Experimental Datasets

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Title Evaluation of Performance of Twelve Color-Difference Formulae Using Two NCSU Experimental Datasets
Title of Series The 5th European Conference on Colour in Graphics, Imaging, and Vision and the 12th International Symposium on Multispectral Colour Science (CGIV 2010/MCS'10)
Part Number 27
Number of Parts 43
Author Shamey, Renzo
Hinks, David
Melgosa, Manuel
Luo, M. Ronnier
Cui, Guihua
Huertas, Rafael
Cárdenas, Lina
Lee, Seung Geol
License CC Attribution - NoDerivatives 2.0 UK: England & Wales:
You are free to use, copy, distribute and transmit the work or content in unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
DOI 10.5446/18261
Publisher River Valley TV
Release Date 2011
Language English
Production Place Joensuu, Finland

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Subject Area Information technology
Abstract We previously reported the performance of four color difference equations around the CIE 1978 blue color center (NCSU-B1) using various statistical measures. In this study we employed the standardized residual sum of squares (STRESS) index to test the performance of twelve color-difference formulae using two experimental NCSU datasets. The first dataset (NCSU-B1) included 66 sample pairs around the CIE 1978 blue color center and the second dataset (NCSU- 2) contained 69 sample pairs around 13 color centers. In the first dataset 26 observers made a total of 5148 assessments of sample pairs with small color differences (ΔE*ab<5) while the second dataset involved 20,700 assessments by 100 observers from four different geographical regions of the world (25 in each region). Each pair in both sets was assessed by each color normal observer in three separate sittings on separate days and the average of assessments was calculated. For the samples in the first dataset a custom AATCC standard gray scale was employed to assess the magnitude of difference between colored samples. A third-degree polynomial equation was used to convert gray scale ratings to visual differences (ΔV). In the second study a novel perceptually linear gray scale was developed and a linear function was used to obtain visual differences. Based on the analysis of STRESS index results the DIN99d equation gave the best results for both datasets, and the CIELAB equation the worst.
Keywords The 5th European Conference on Colour in Graphics, Imaging
Vision and the 12th International Symposium on Multispectral Colour Science

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