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Article

Accuracy and Reliability of Smartphone Versus Mirrorless Camera Images-Assisted Digital Shade Guides: An In Vitro Study

by
Soo Teng Chew
1,
Suet Yeo Soo
1,
Mohd Zulkifli Kassim
1,
Khai Yin Lim
2 and
In Meei Tew
1,*
1
Department of Restorative Dentistry, Faculty of Dentistry, The National University of Malaysia, Jalan Raja Abdul Aziz, Kuala Lumpur 50300, Malaysia
2
Department of Research and Development, Tunku Abdul Rahman University of Management and Technology, Lorong Lembah Permai 3, Pulau Pinang 11200, Malaysia
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(14), 8070; https://doi.org/10.3390/app15148070
Submission received: 6 June 2025 / Revised: 15 July 2025 / Accepted: 17 July 2025 / Published: 20 July 2025
(This article belongs to the Special Issue Advances in Dental Materials, Instruments, and Their New Applications)
Browse Figures
Versions Notes

Abstract

Image-assisted digital shade guides are increasingly popular for shade matching; however, research on their accuracy remains limited. This study aimed to compare the accuracy and reliability of color coordination in image-assisted digital shade guides constructed using calibrated images of their shade tabs captured by a mirrorless camera (Canon, Tokyo, Japan) (MC-DSG) and a smartphone camera (Samsung, Seoul, Korea) (SC-DSG), using a spectrophotometer as the reference standard. Twenty-nine VITA Linearguide 3D-Master shade tabs were photographed under controlled settings with both cameras equipped with cross-polarizing filters. Images were calibrated using Adobe Photoshop (Adobe Inc., San Jose, CA, USA). The L* (lightness), a* (red-green chromaticity), and b* (yellow-blue chromaticity) values, which represent the color attributes in the CIELAB color space, were computed at the middle third of each shade tab using Adobe Photoshop. Specifically, L* indicates the brightness of a color (ranging from black [0] to white [100]), a* denotes the position between red (+a*) and green (–a*), and b* represents the position between yellow (+b*) and blue (–b*). These values were used to quantify tooth shade and compare them to reference measurements obtained from a spectrophotometer (VITA Easyshade V, VITA Zahnfabrik, Bad Säckingen, Germany). Mean color differences (∆E00) between MC-DSG and SC-DSG, relative to the spectrophotometer, were compared using a independent t-test. The ∆E00 values were also evaluated against perceptibility (PT = 0.8) and acceptability (AT = 1.8) thresholds. Reliability was evaluated using intraclass correlation coefficients (ICC), and group differences were analyzed via one-way ANOVA and Bonferroni post hoc tests (α = 0.05). SC-DSG showed significantly lower ΔE00 deviations than MC-DSG (p < 0.001), falling within acceptable clinical AT. The L* values from MC-DSG were significantly higher than SC-DSG (p = 0.024). All methods showed excellent reliability (ICC > 0.9). The findings support the potential of smartphone image-assisted digital shade guides for accurate and reliable tooth shade assessment.

1. Introduction

Accurate tooth shade selection is a challenging process in aesthetic dentistry [1], especially with the conventional visual shade selection methods using shade guides. Color mismatches in the conventional shade-matching method can arise from significant variations in natural tooth color and surface characteristics [2], as well as discrepancies in color perception among clinicians and technicians. Furthermore, factors such as the observer’s age, experience, eye fatigue, color blindness, and lighting conditions [3,4,5], further contribute to the unreliable conventional shade matching outcomes [6], which results in greater patient dissatisfaction [3].
On the other hand, instrumental shade-matching devices, such as spectrophotometers and colorimeters, provide an objective approach to shade selection, addressing the limitations associated with the conventional shade selection method [6]. Among these instrumental shade-matching devices, spectrophotometers have been shown to offer more reliable measurements because of their ability to analyze light reflection across the entire visible spectrum [7]. However, spot measurement spectrophotometers such as VITA Easyshade V, with their small measurement window, can restrict the assessment of a natural tooth’s overall color [8,9]. In addition, spectrophotometers tend to be expensive and are not always readily available in clinical settings [9].
The advancement of photography and computing has led to the development of image-based digital shade guides, which serve as an effective alternative to contact-type instrumental shade-matching devices [6,10,11,12,13] in improving shade-matching accuracy [14,15]. High resolution digital photographs enable the reproduction of the entire tooth color spectrum and unique tooth surface characteristics [16], thus facilitating communication between clinicians and technicians [12,17]. In previous studies, digital single-lens reflex (DSLR) cameras have been commonly used for capturing high resolution images in dental shade matching [12,17,18,19]. Nevertheless, there is a growing trend toward mirrorless camera systems, which offer advantages such as greater compactness, lighter weight, and faster autofocus, along with improved light exposure optimization [20]. These mirrorless cameras, equipped with high resolution sensors, excel in capturing fine details and textures within the oral cavity [21]. Key improvements in image quality include back-illuminated sensors that enhance performance in low-light conditions and in-body image stabilization that minimizes blurriness by stabilizing across multiple axes [20].
Alternatively, smartphone cameras, which are highly accessible, have gained popularity in dental photography. Improvements in smartphone camera technology have significantly enhanced image quality, making them comparable to those taken by DSLR cameras [22,23]. In a study by Moussa et al. [24], the linear measurements of plaster models photographed with both a DSLR and a smartphone camera were found to have no statistically significant differences. Smartphone cameras with accurate edge positioning and radiometry allow for good quality and well-defined images with correct color reproduction as compared to a DSLR camera [25]. Jorquera et al. [6] also found that when equipped with suitable light-correction filters, smartphones provided shade selection results comparable to those achieved with digital cameras for color assessment of ceramic crowns.
The CIELAB system is widely used in dentistry because of its adaptive chromatic basis, which facilitates quantification of reflected light [26,27,28]. This system helps to determine the color coordinates L* (luminosity, from black to white), a* (chromaticity along the red-green axis), and b* (chromaticity along the yellow-blue axis) [29]. The color difference (ΔE) formula has been adopted as the standard to measure the color difference between two objects [30]. CIEDE2000 color difference (ΔE00), as an improved version of ΔEab, is well recommended by the International Commission on Illumination (CIE) for total color difference computation because of its high accuracy and repeatability [31]. In dentistry, color differences (∆E) are quantitatively assessed against established thresholds to determine clinical relevance. AT is a magnitude of color difference that is acceptable for the aesthetic outcome, while PT refers to the smallest color difference the human eye can detect [32]. Based on a comprehensive review by Paravina et al. [33], PT values typically range from 0.8 to 1.7, while AT values vary from 1.8 to 3.7, depending on variables such as observer type, lighting conditions, and material characteristics. Despite this range, the values ΔE00 = 0.8 for PT and ΔE00 = 1.8 for AT are widely accepted as standard reference points in controlled in vitro studies involving dental ceramics.
To date, there is a lack of studies investigating the potential use of image-based digital shade guides in dental shade matching. Hence, this study aims to construct two image-assisted digital versions of the VITA Linearguide, using calibrated images of its shade tabs captured with a mirrorless camera (MC-DSG) and smartphone camera (SC-DSG), respectively. Furthermore, this study also assesses the color differences, accuracy, and reliability of MC-DSG and SC-DSG as compared to a spectrophotometer. The first null hypothesis was that there were no significant differences in color measurement among MC-DSG, SC-DSG, and the spectrophotometer. The second null hypothesis was that there were no significant differences in accuracy among MC-DSG, SC-DSG, and spectrophotometer. The third null hypothesis was that there were no significant differences in reliability among MC-DSG, SC-DSG, and spectrophotometer.

2. Materials and Methods

2.1. Study Design

This in vitro study was conducted in the Faculty of Dentistry at the National University of Malaysia.

2.2. Digital Imaging of Shade Tabs

The images of 29 shade tabs of VITA Linearguide 3D-Master (VITA Zahnfabrik, Bad Säckingen, Germany) were each taken by a mirrorless camera (Canon EOS RP) and a smartphone camera (Samsung S23 Ultra) to develop MC-DSG (Figure 1) and SC-DSG (Figure 2), respectively, following the equipment and predetermined parameters listed in Table 1.
During the photography of the shade tabs, each shade tab was mounted on a fixed black cardboard, while the mirrorless camera was attached to a tripod positioned 19 cm from the shade tab. The images of each shade tab were taken in a controlled room under standardized lighting (5500 K color temperature) [34,35] with pre-set photography parameters. Both cameras were equipped with cross-polarizing filters to reduce surface glare during image capture.
The camera’s custom white balance (CWB) was manually configured by capturing an image of the gray reference card (WhiBal Gray Cards, Michael Tapes Design) [36]. The gray reference card was photographed alongside the shade tab [37] for further white balance analysis, ensuring consistent color calibration across all images. All images were taken at one-minute intervals to ensure consistent flash brightness [9]. This procedure was subsequently repeated with the smartphone camera. To test the reliability of the digital shade guides, each shade tab was photographed three times, resulting in a total of 87 images of shade tabs taken for MC-DSG and SC-DSG, respectively [35].

2.3. Shade Tab Image Processing

All images captured with the mirrorless camera were saved in RAW file format [38], while those with the smartphone camera were saved in the default JPEG format, with dimensions of 2108 × 2108 pixels, and subsequently converted into bitmap format [39]. All the images from both mirrorless and smartphone cameras were imported into Adobe Photoshop 2023 (version 24.7) for cropping and color value (L*, a*, b*) measurements after white balancing using a standard gray reference card. The brightness of the image was corrected by modifying its exposure until the gray card’s measured luminosity matched its reference value (L* = 75, a* = 0, b* = 0) [19].

2.4. Color Measurement

To measure the color of the shade tab images, the L*, a*, and b* values were measured at the midpoint of each shade tab, where the point was intersected between two lines oriented in the inciso-apical and mesiodistal directions (Figure 3). Each measurement was repeated three times, and the mean values of L*, a*, and b* for each shade tab were calculated for both MC-DSG and SC-DSG.
For the color measurement of all 29 VITA Linearguide 3D-Master shade tabs, the spectrophotometer (VITA Easyshade V, VITA Zahnfabrik) was used as the reference standard. During measurement, the device tip was positioned perpendicular to the middle third of each shade tab to ensure consistent readings. Before each session, the spectrophotometer was calibrated by placing the tip on the calibration block, following the manufacturer’s guidelines. The CIE L*, a*, and b* values were then recorded for analysis. Three measurements were taken for each shade tab, and the mean L*, a*, and b* values for each shade tab were calculated [40].
The CIELAB coordinates (L*, a*, b*) were converted to the cylindrical CIELCH system to determine chroma (C*) and hue angle (H*). Chroma was calculated as C* = √ (a*2 + b*2), and hue angle as H* = a tan2 (b*, a*), expressed in degrees from 0° to 360°. These values were then used in the CIEDE2000 (ΔE00) color difference formula, in line with the standard method recommended by the International Commission on Illumination (CIE) [26]. The color differences (ΔE00) between both MC-DSG and SC-DSG and the spectrophotometer reference were calculated using the following equation:
Δ E 00 =   Δ L ∗ k L S L 2 + Δ C ∗ k C S C 2 + Δ H ∗ k H S H 2
In this formula, ΔL* represents the difference in lightness, ΔC* indicates the chroma difference, and ΔH* is the hue difference between the compared samples. The terms kL, kC, and kH are parametric correction factors, which were each set to 1 as recommended for standard conditions. SL, SC, and SH are weighting functions that adjust the influence of lightness, chroma, and hue on perceived color differences.

2.5. Statistical Analysis

Statistical analysis was performed using a statistical software program (SPSS version 29, IBM Corp., New York, NY, USA). Differences in L*, a*, and b* values between groups were evaluated using one-way ANOVA, followed by Bonferroni post hoc tests for multiple pairwise comparisons. Mean color differences (∆E00) between the MC-DSG and SC-DSG in comparison to the spectrophotometer were analyzed using an independent t-test. Furthermore, the magnitude of ∆E00 values between the MC-DSG and SC-DSG in comparison to the spectrophotometer was compared against PT of 0.8 and AT of 1.8 as reference standards.
For reliability, the photographs of all shade tabs were retaken using both mirrorless and smartphone cameras under identical parameters for consecutive weeks. The reliability of the MC-DSG, SC-DSG, and spectrophotometer was assessed using the Intraclass Correlation Coefficient (ICC), based on a two-way mixed-effect model with absolute agreement and single measurements. The interpretation of ICC values followed the thresholds: <0.50 = poor, 0.50–0.75 = moderate, 0.75–0.90 = good, and >0.90 = excellent [41]. The results were then compared using one-way ANOVA with Bonferroni post hoc tests. The agreement between both MC-DSG and SC-DSG with spectrophotometer was further analyzed using the Bland–Altman test. The significance value was set at α = 0.05.

3. Results

3.1. Comparative Accuracy of Smartphone and Mirrorless Camera Images-Assisted Digital Shade Guides

Mean Color Difference (∆E00)

A total of 29 images were captured, each using a mirrorless camera and a smartphone camera. The comparison of mean L*, a*, and b* values among SC-DSG, MC-DSG, and spectrophotometer is shown in Figure 4. Multiple pairwise comparisons revealed that MC-DSG had significantly higher mean L* values than SC-DSG (p = 0.024) and higher a* values than the spectrophotometer (p = 0.013). The comparison of ∆E00 between MC-DSG and SC-DSG relative to the spectrophotometer is shown in Figure 5. SC-DSG exhibited significantly lower mean ∆E00 values as compared to MC-DSG (p < 0.001). When compared to PT and AT, MC-DSG exceeded both AT and PT for ∆E00 values. In contrast, SC-DSG showed color differences that remained within acceptable limits, with its ∆E00 values close to the AT of 1.8.

3.2. Reliability Analysis

3.2.1. Inter-Device Reliability

The Intraclass Correlation Coefficients of CIELAB values of MC-DSG, SC-DSG, and VITA Easyshade V are presented in Table 2. All three digital shade-matching devices showed excellent reliability with ICC > 0.9 for L*, a*, and b* values. However, when comparing the reliability among the three devices, the MC-DSG showed significantly lower reliability than the spectrophotometer in a* (p = 0.024) and b* (p = 0.002) values. Additionally, SC-DSG also had significantly lower reliability in b* value (p = 0.004) as compared to VITA Easyshade V.

3.2.2. Intra-Examiner Reliability

Intra-examiner reliability testing was performed with Cronbach’s alpha of 0.996, indicating excellent consistency and reliability of CIE L*a*b* coordinate measurements.

3.3. Agreement Analysis

The Bland–Altman scatterplot between the MC-DSG and SC-DSG with a spectrophotometer is presented in Figure 6. The SC-DSG showed a better agreement with the VITA Easyshade V, exhibiting less bias and showing minimal signs of proportional bias across all datasets.

4. Discussion

Digital imaging systems are gaining popularity for dental shade selection. However, the accuracy and precision of image-assisted digital shade guides vary depending on the types of cameras used, camera settings, and photography protocols [31]. Hence, this study compared the color differences, accuracy, and reliability of two image-assisted digital versions of VITA 3D-Master Linearguide (MC-DSG and SC-DSG) with VITA Easyshade V as a control. The null hypotheses were rejected, indicating significant color differences, accuracy, and reliability among MC-DSG, SC-DSG, and VITA Easyshade V.
In this study, image-based digital shade guides were constructed based on the VITA 3D-Master Linearguide, which provides a broader color range and a more uniform color distribution than the Vitapan Classical [42]. The enhanced shade matching accuracy provided by the linearly arranged VITA 3D-Master Linearguide shade tabs [43] has the potential to make image-based digital shade guides a more reliable tool in clinical practice. This digital shade guide, however, remains largely unexplored and warrants further investigation.
A spectrophotometer was used in this study as a control due to its well-documented superior repeatability and accuracy across multiple studies [8,44,45,46]. Compared to the spectrophotometer, the color differences, ∆E00, observed in SC-DSG were significantly lower than those in MC-DSG. This highlights the advantages of using a higher resolution smartphone camera (200-megapixel) with a cross-polarized filter and light-correcting device to develop a digital shade guide with enhanced trueness in shade measurements. This is in line with the findings of Sirintawat et al. [35], which demonstrated that a smartphone camera with similar photography equipment and parameters achieved accuracy comparable to that of a spectrophotometer. Conversely, Sampaio et al. [9] reported the least accuracy when using a smartphone without a cross-polarized filter and light-correcting device, in contrast to a DSLR camera with different flashes and a cross-polarized filter.
SC-MSG outperformed MC-MSG in providing more consistent results and achieving a higher acceptable aesthetic outcome, with AT values approaching the threshold of 1.8. Additionally, SC-MSG demonstrated the potential to reduce color mismatch, with ∆E00 values close to clinically acceptable limits. This may be attributed to the attachment of a light-correcting device on the smartphone camera, which ensures uniform lighting conditions for the captured images [47,48]. Hence, the consistency in lighting helps to overcome the issue of unstable illumination, which causes variations in the color characteristics, as reported by Tam et al. [39].
The means of CIE L*a*b* color coordinates of each shade tab were compared across three groups in this study. Among these dimensions, luminosity (L*) was considered the most critical factor influencing perceptible color changes in shade matching [49,50,51]. The results of this study demonstrated that SC-DSG showed better agreement with the spectrophotometer for the L* value as compared to MC-DSG. However, the mean L* value in MC-DSG was significantly higher than in SC-DSG, with greater deviations from the spectrophotometer. According to Sahin and Ural [52], an increased L* value can lead to more pronounced color mismatches, which may affect the clinical accuracy of shade matching. The high L* value observed in MC-DSG was likely due to the larger pixel areas on the full-frame sensor of a mirrorless camera, which enhances light capture [53] as compared to a smartphone camera. Additionally, the use of ISO settings above the commonly used baseline of 100 [19,54] in MC-DSG compensates for the low lighting conditions but also results in increased image exposure. Therefore, fine-tuning the ISO setting is necessary for more accurate color validation in future studies.
In this study, all three study groups demonstrated excellent intra-device repeatability. Nevertheless, the spectrophotometer proved to be a more reliable shade-matching instrument as compared to SC-DSG and MC-DSG. The superior reliability of the spectrophotometer is likely attributed to its use of an internal light source, as opposed to the standardized external ambient light sources used by the SC-DSG and MC-DSG. This observation is further supported by Nantanapiboon et al. [55], who reported that the spectrophotometer exhibited almost perfect reliability when using the device’s light source alone or in combination with room lighting.
A two-step white balance calibration process was employed in this study to enhance the color accuracy of each photographed shade tab. This involved using a white balance gray card for calibration both within the photographic device and during the image processing phase. The manual white balance calibration method was preferred in this study as it minimizes the influence of undesirable environmental light and significantly improves digital color accuracy compared to automatic white balance correction [56]. These findings align with those of Tung et al. [36], who reported a 26% improvement in shade-matching accuracy when using a digital shade guide with a custom white balance. Furthermore, post-processing white balance adjustments in Photoshop further refine color accuracy, allowing for precise fine-tuning of the image to achieve optimal color representation, which is particularly valuable when dealing with complex lighting conditions [57,58].
In recent years, numerous mobile applications for shade matching have been introduced in clinical dentistry, providing a convenient means to assist visual shade selection. However, many of these applications rely heavily on in-app camera settings and ambient lighting conditions, which may introduce inconsistencies in color capture [6]. In contrast, this study used standardized photography parameters, cross-polarizing filters, and post-processing calibration to improve color accuracy and reproducibility in clinical shade assessment [16,59].
Several limitations have been identified in this study. Only one type of digital camera and smartphone camera was used for constructing image-assisted digital shade guides. Future studies are needed to explore the effectiveness of image-assisted digital shade guides constructed by different types of cameras with standardized photography parameters on shade matching accuracy, especially in clinical settings. This study used standardized camera settings, cross-polarizing filters, and a WhiBal gray card to set a custom white balance for each photography session. While this practical calibration helps reduce color variation, full device-specific camera profiling was not performed. This may limit cross-device consistency and highlights the need for more advanced calibration methods in future studies to ensure consistent color capture across devices. Additionally, the in vitro setting may not fully replicate clinical lighting conditions, and shade matching on natural teeth may introduce further variables. Moreover, the color measurement on the incisal and gingival third of the shade tab should be taken into consideration for a more comprehensive color accuracy assessment. Future studies should apply the image-assisted digital shade guide on natural teeth, which exhibit more complex and variable optical properties, to more effectively assess its accuracy and reliability in clinical shade matching.

5. Conclusions

Within the limitations of this study, the image-assisted digital shade guides constructed using images obtained from a smartphone camera (SC-DSG) demonstrated significantly higher accuracy than those obtained from a mirrorless camera (MC-DSG), with an acceptable mean color difference of ∆E00 = 1.8 and closer agreement with the VITA Easyshade V, suggesting SC-DSG has potential as an accessible and effective tool for dental shade matching. While MC-DSG, SC-DSG, and VITA Easyshade V demonstrated excellent overall reliability, the VITA Easyshade V showed superior reliability, particularly for a* and b* values.

Author Contributions

Conceptualization, S.T.C. and I.M.T.; methodology, S.T.C.; software, S.T.C.; validation, S.T.C.; formal analysis, S.T.C.; investigation, S.T.C.; resources, S.T.C.; data curation, S.T.C.; writing—original draft preparation, S.T.C.; writing—review and editing, S.T.C., I.M.T., S.Y.S., M.Z.K. and K.Y.L.; visualization, S.T.C. and I.M.T.; supervision, I.M.T., S.Y.S., M.Z.K. and K.Y.L.; project administration, S.T.C.; funding acquisition, S.T.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data presented in this study are available on request from the corresponding authors.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
MC-DSGMirrorless Camera Digital Shade Guide
SC-DSGSmartphone Camera Digital Shade Guide
CIECommision International de l’Éclairage

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Applsci 15 08070 g001
Figure 1. Shade tab images of MC-DSG. The alphanumeric codes below each shade tab indicate the designated shades from the VITA Linearguide 3D-Master system. Step 1 shows the first stage of the shade selection process, where the correct value group (lightness) is determined; Step 2 illustrates that the appropriate chroma level is determined within the selected value group, and slight hue adjustments are made if required to achieve the closest match.
Figure 1. Shade tab images of MC-DSG. The alphanumeric codes below each shade tab indicate the designated shades from the VITA Linearguide 3D-Master system. Step 1 shows the first stage of the shade selection process, where the correct value group (lightness) is determined; Step 2 illustrates that the appropriate chroma level is determined within the selected value group, and slight hue adjustments are made if required to achieve the closest match.
Applsci 15 08070 g001
Applsci 15 08070 g002
Figure 2. Shade tab images of SC-DSG. The alphanumeric codes below each shade tab indicate the designated shades from the VITA Linearguide 3D-Master system. Step 1 shows the first stage of the shade selection process, where the correct value group (lightness) is determined; Step 2 illustrates that the appropriate chroma level is determined within the selected value group, and slight hue adjustments are made if required to achieve the closest match.
Figure 2. Shade tab images of SC-DSG. The alphanumeric codes below each shade tab indicate the designated shades from the VITA Linearguide 3D-Master system. Step 1 shows the first stage of the shade selection process, where the correct value group (lightness) is determined; Step 2 illustrates that the appropriate chroma level is determined within the selected value group, and slight hue adjustments are made if required to achieve the closest match.
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Figure 3. Color measurements of L*, a*, and b* values at the middle of the shade tab using Adobe Photoshop.
Figure 3. Color measurements of L*, a*, and b* values at the middle of the shade tab using Adobe Photoshop.
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Figure 4. Mean values of L*, a*, and b* of MC-DSG, SC-DSG, and VITA Easyshade V. The error bars indicate the mean ± 1 standard deviation. m significant difference in L* between MC-DSG and SC-DSG, p < 0.05. n significant difference in a* between MC-DSG and VITA Easyshade V, p < 0.05.
Figure 4. Mean values of L*, a*, and b* of MC-DSG, SC-DSG, and VITA Easyshade V. The error bars indicate the mean ± 1 standard deviation. m significant difference in L* between MC-DSG and SC-DSG, p < 0.05. n significant difference in a* between MC-DSG and VITA Easyshade V, p < 0.05.
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Figure 5. Mean and SD values of the CIEDE2000 color difference (ΔE00) between both MC-DSG and SC-DSG with VITA Easyshade V. The error bars indicate the mean ± 1 standard deviation. The dashed line indicates the perceptibility (PT) threshold (ΔE00 = 0.8), while the solid line marks the acceptability (AT) threshold (ΔE00 = 1.8).
Figure 5. Mean and SD values of the CIEDE2000 color difference (ΔE00) between both MC-DSG and SC-DSG with VITA Easyshade V. The error bars indicate the mean ± 1 standard deviation. The dashed line indicates the perceptibility (PT) threshold (ΔE00 = 0.8), while the solid line marks the acceptability (AT) threshold (ΔE00 = 1.8).
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Figure 6. Bland–Altman scatterplot. (A), differences of L* between MC-DSG and VITA Easyshade V. (B), differences of L* between SC-DSG and VITA Easyshade V. (C), differences of a* between MC-DSG and VITA Easyshade V. (D), differences of a* between SC-DSG and VITA Easyshade V. (E), differences of b* between MC-DSG and VITA Easyshade V. (F), differences of b* between SC-DSG and VITA Easyshade V. In each Bland–Altman plot, the middle line represents the mean difference between methods, while the upper and lower lines represent the 95% limits of agreement, calculated as the mean difference ± 1.96 standard deviations.
Figure 6. Bland–Altman scatterplot. (A), differences of L* between MC-DSG and VITA Easyshade V. (B), differences of L* between SC-DSG and VITA Easyshade V. (C), differences of a* between MC-DSG and VITA Easyshade V. (D), differences of a* between SC-DSG and VITA Easyshade V. (E), differences of b* between MC-DSG and VITA Easyshade V. (F), differences of b* between SC-DSG and VITA Easyshade V. In each Bland–Altman plot, the middle line represents the mean difference between methods, while the upper and lower lines represent the 95% limits of agreement, calculated as the mean difference ± 1.96 standard deviations.
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Table 1. The categorization of photographic equipment with standardized parameters.
Table 1. The categorization of photographic equipment with standardized parameters.
GroupStandardized ParametersEquipmentManufacturers
MC-DSGShutter speed (1/125 s), aperture (f22), ISO (320), flash (1/1), custom white balance, focusing (1:1), distance (19 cm)Mirrorless camera (Canon EOS R)Applsci 15 08070 i001Canon, Tokyo, Japan
Macro lens (Canon RF 100 mm 2.8 L)Applsci 15 08070 i002Canon, Tokyo, Japan
Twin flash (Godox MF12 Twin Flash)Applsci 15 08070 i003Godox, Shenzen, China
Cross-polarized filter (Polar eyes)Applsci 15 08070 i004Bioemulation, Freiburg im Breisgau, Germany
SC-DSGShutter speed (1/180 s), aperture (f1.7), ISO (160), no flash, custom white balance, focusing (1:1), distance (19 cm)Smartphone (Galaxy S24 Ultra)Applsci 15 08070 i005Samsung, Seoul, Republic of Korea
Cross-polarized filter + Light-correcting device (Smile Lite MDP2)Applsci 15 08070 i006Smile Line, St-Imier, Switzerland
WhiBal CardWhite balance gray cardApplsci 15 08070 i007WhiBal, Michael Tapes Design, Florida, USA
VITA EasyShade Advance VSpectrophotometerApplsci 15 08070 i008VITA Zahnfabrik, Bad Säckingen,
Germany
VITA Linearguide 3D-MasterShade guideApplsci 15 08070 i009VITA Zahnfabrik, Bad Säckingen,
Germany
Table 2. Intraclass correlation coefficients of CIE L*a*b* values among MC-DSG, SC-DSG, and VITA Easyshade V.
Table 2. Intraclass correlation coefficients of CIE L*a*b* values among MC-DSG, SC-DSG, and VITA Easyshade V.
MeasurementsType of DevicesIntraclass Correlation95% Confidence Intervalp-Value
Lower BoundUpper Bound
L* valueMC-DSG0.9960.9920.9980.374
SC-DSG0.9970.9940.998
VITA Easyshade V0.9990.9911.000
a* valueMC-DSG0.968 a0.9420.9840.022 *
SC-DSG0.9800.9630.990
VITA Easyshade V0.999 a0.9991.000
b* valueMC-DSG0.985 b0.9620.999<0.001 *
SC-DSG0.994 c0.9710.999
VITA Easyshade V0.999 b,c0.9991.000
* Significant differences among MC-DSG, SC-DSG, and VITA Easyshade V, p < 0.05. a Significant difference between MC-DSG and VITA Easyshade V in a* value, p < 0.05. b Significant difference between MC-DSG and VITA Easyshade V in b* value, p < 0.05. c Significant difference between SC-DSG and VITA Easyshade V in b* value, p < 0.05.
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Chew, S.T.; Soo, S.Y.; Kassim, M.Z.; Lim, K.Y.; Tew, I.M. Accuracy and Reliability of Smartphone Versus Mirrorless Camera Images-Assisted Digital Shade Guides: An In Vitro Study. Appl. Sci. 2025, 15, 8070. https://doi.org/10.3390/app15148070

AMA Style

Chew ST, Soo SY, Kassim MZ, Lim KY, Tew IM. Accuracy and Reliability of Smartphone Versus Mirrorless Camera Images-Assisted Digital Shade Guides: An In Vitro Study. Applied Sciences. 2025; 15(14):8070. https://doi.org/10.3390/app15148070

Chicago/Turabian Style

Chew, Soo Teng, Suet Yeo Soo, Mohd Zulkifli Kassim, Khai Yin Lim, and In Meei Tew. 2025. "Accuracy and Reliability of Smartphone Versus Mirrorless Camera Images-Assisted Digital Shade Guides: An In Vitro Study" Applied Sciences 15, no. 14: 8070. https://doi.org/10.3390/app15148070

APA Style

Chew, S. T., Soo, S. Y., Kassim, M. Z., Lim, K. Y., & Tew, I. M. (2025). Accuracy and Reliability of Smartphone Versus Mirrorless Camera Images-Assisted Digital Shade Guides: An In Vitro Study. Applied Sciences, 15(14), 8070. https://doi.org/10.3390/app15148070

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