Does background color influence visual thresholds?
Introduction
Visual thresholds for color discrimination are well-established quality control tools in research and industry. Thus, according to the latest Guidance on color measurements, published by the International Organization for Standardization ISO/TR 28642:2016 [1], color variation should be assessed based on comparisons with 50:50 % thresholds. Perceptibility difference threshold (PT) represents the lower perceptual limit and it can be used for studying discernible colors by the human visual system [2]. However, in many practical situations, noticeable to greater differences above PT, which are still considered as tolerable or acceptable, are limited by the acceptability threshold (AT). The interest on these differences is mostly justified by the need to keep differences under an admissible limit in clinical practice and particularly for industrial production control.
A recent study [3] provided an extensive literature review on thresholds of color difference for dentistry and dental applications using diverse color difference metrics. Some of such studies [4,5] have shown that AT and PT values are significantly different using CIELAB (ΔE*ab) and CIEDE2000(1:1:1) (ΔE00(1:1:1)) color difference metrics. In addition, it has been shown [5,6] that patients are less discriminating and critical than dentists regarding color differences.
A previous study [7] has shown that CIEDE2000(2:1:1) (ΔE00(2:1:1)) metric shows better agreement with visual judgments in restorative dentistry. However, up to this moment, there is no study establishing the values of PT and AT using this metric.
Background is defined as the surface upon which samples are placed along with the environment extending for about 10° from the edge of stimulus in all or most directions [1]. In dental clinical practice, the background is often represented by the darkness of the oral cavity. However, there is a wide range of studies that have used either black [4,[7], [8], [9], [10]], grey [5,11,12] or white backgrounds [[13], [14], [15]] to evaluate color and color differences in dentistry. Also, it is noteworthy that the International Organization for Standardization, ISO/TR 28642:2016 [1], does not recommend the use of a specific background for visual and instrumental color assessment. Therefore, black, white and grey backgrounds have been used to evaluate color of natural teeth, to evaluate and interpreting clinical outcomes and, particularly, as a quality control tool and guide to evaluate and select dental materials.
Although the influence of the background on color perception in dentistry has been reported [[16], [17], [18], [19]], no consensus has been reached to the adequate background. An in vitro study [16] found that white and black backgrounds produced the best results for shade matching. However, another study [17] showed that black and grey backgrounds better simulate an intraoral environment than the white background. Although the influence of background is often considered an important parameter for color matching in restorative dentistry, there are no studies determining and quantifying the influence on perceptual and admissible limits of color differences. Moreover, the research protocol designed to establish PT and AT values for dental applications have used only the neutral grey as the color background [5].
Therefore, the purpose of this study was to evaluate the influence of neutral color backgrounds on visual thresholds (PT and AT) using ΔE*ab, ΔE00(1:1:1) and ΔE00(2:1:1) color difference metrics. Testing the hypotheses that (1) background color influences the 50:50 % visual color thresholds, and (2) color difference metrics produce a significant different performance on evaluating visual color differences in dentistry.
Section snippets
Stimuli and psychophysical experiments
CIELAB color coordinates of monochromatic ceramics specimens reported by Paravina et al. [5] were used to represent simulated upper central incisors (SUCI). According to that study [5], a total of 60 SUCI pairs were selected for psychophysical experiment and the same distribution of the color differences pairs was used. The CIE L*a*b* color coordinate range values for simulated teeth were as follows: L* = 64.2–76.8; a* = 1.7–7.5, and b* = 14.3–27.8.
Three different achromatic backgrounds were
Results
The 50:50 % PT, 50:50 % AT, 95 % confidence intervals (for all observers) using ΔE*ab, ΔE00(1:1:1), and ΔE00(2:1:1) over the three backgrounds are presented in Table 1. Statistical grouping for PT and AT for each background and metric is also included in Table 1.
Considering all observers (Table 1), the 50:50 % PT values over white and grey backgrounds were significantly lower than over black background for each color difference metrics (p ≤ 0.05). The 50:50 % AT values over the white background
Discussion
Color thresholds values should be used to interpret clinical and dental laboratory situations in terms of perceptibility and/or acceptability of color differences between natural teeth and dental restorations, or to assess color changes of discolored and/or bleached dental structures. Due to the subjectivity of visual shade selection, dental color determination is influenced by many factors [1], which include the background. The influence of the background on color perception in dentistry has
Conclusion
Within the limitations of the present computer simulated study, results suggest that the color of the background significantly influenced the perceptibility and acceptability thresholds. Color mismatch between a restoration and the adjacent dental structure is more difficult to be accepted over a white background. Color difference metrics influenced the PT and AT values over all color backgrounds. Further studies on efficacy of color difference formulas, different observation conditions and
CRediT authorship contribution statement
María M. Pérez: Methodology, Investigation, Writing - original draft, Resources, Supervision. Alvaro Della Bona: Conceptualization, Investigation, Writing - review & editing, Resources, Supervision. Francisco Carrillo-Pérez: Software, Validation, Formal analysis. Diana Dudea: Investigation, Resources. Oscar E. Pecho: Investigation, Resources. Luis Javier Herrera: Formal analysis, Writing - original draft.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
Special thanks to the observers who took part in this study. The authors acknowledge funding support from the Spanish Ministry of Science, Innovation and Universities (PGC2018-101904-A-100 and RTI2018-101674-B-I00), from the University of Granada, Spain (A.TEP.280.UGR18), and from CNPq do Brasil (302587/2017-9).
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