## 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, \(\Delta\)E\({}_{00}\), 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 [PERSON] et al. [35], which demonstrated that a smartphone camera with similar photography equipment and parameters achieved accuracy comparable to that of a spectrophotometer. Conversely, [PERSON] 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. 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 \(\pm\) 1.96 standard deviations. 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 \(\Delta\)E\({}_{00}\) 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 [PERSON] 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.