Importance of Calibration of Photos Obtained by A Smartphone in Facial Prosthesis

Aiming at the difficulty of manufacturing a facial prosthesis that has the exact color of the patientâ€™s skin...


Methods:
We used a Samsung Galaxy S8+ smartphone having two polarized light filters that were positioned perpendicularly on the camera and flash, and the reference element, which is an A2 color sample of the VITA-PAN color scale. Three patients were photographed carrying a facial prosthesis and holding the reference element over their faces. Using the software program Adobe PhotoShopCC, the photographs were calibrated according to the known L*a*b* values of the A2 color sample, and five points were selected on the original photograph and the photograph was calibrated for comparison, totaling 30 points. The tonalities were compared numerically according to the formula ( ) ( ) ( ) The intraclass correlation test was applied to determine the concordance between the photos before and after calibration. Furthermore, the Student t-test for paired samples was applied to determine differences in the mean values of the studied parameters before and after calibration. The statistical program SPSS 2.1 was used, adopting α = 0.05.

Results:
In relation to the editing of the photographs, the statistical analysis revealed a significant difference in L* and a* values before and after calibration, while in the b* value, there was no significant change in color.

Conclusion:
Based on the results, it is concluded that the proposed standardization technique, using polarized light filters and calibration with a reference element, of photographs obtained using a smartphone camera is appropriate for distinguishing colors in the production of facial prostheses.
Clinical Implication: This new methodology can be used to increase the reliability of the smartphone as a tool for the manufacture of the facial prosthesis.
condition [3][4][5]. Facial prostheses are made from silicone, due to its excellent properties of flexibility, texture, and color, which are similar to those of natural skin [6]. However, one of the main difficulties in the manufacture of such prostheses is obtaining a color tone that closely matches color tone of the patient's own skin. Color is a response to the physical interaction of light energy with an object and the subjective experience of an observer, being characterized as a psychophysical event [7]. Color can be defined as the appearance of any object that can be reproduced in terms of hue, luminosity, and saturation. The Commission Internacionale de l'Eclairage created the L*a*b* color system in 1974. The system identifies the colors numerically, whereby "L" is the brightness coordinate (ranging from 0 to 100 on a scale from darker to lighter tone), "a" is the red-green coordinate (the higher "a" is, the redder the hue, and the lower "a" is, the greener the hue) and "b" is the yellow-blue coordinate (the higher "b" is, the yellowish the hue, and the lower "b" is, the bluer the hue) [8].
The color of an object can be captured both instrumentally and visually [9]. By the instrumental method, a high-precision device called a spectrophotometer can be used to obtain the correct data on the tonality to be captured. This method has the advantage of being more decisive, and possible environmental interference in the color capture can be controlled. However, this equipment is costly.
The visual method is the one currently used for the manufacture of facial prostheses and involves comparison of the color of an object with a color scale or reference. It is a simple method, but it is susceptible to factors that can affect the correct color recognition, such as the brightness of an object, the professional's experience and age, vision fatigue, and color blindness [10]. This discrepancy in capturing the actual color of the patient's skin can lead to errors, with the prosthesis having to be remade, incurring higher material cost and a longer time to complete the work. These discrepancies may be even more important when 3D digital workflows, which include 3D models of faces obtained by optical resources, will evolve into color 3D printing for final facial prosthesis delivery, like the PlusID (+ID) methodology which uses smartphones and "UV maps" from monoscopic photogrammetry to obtain the color information of the face of the patient [11,12]. In view of the high cost of these instruments for accurate color capture, they are not widely used in rehabilitation centers, especially in those with fewer investments. Therefore, it is important to develop research to produce devices for capturing color that are lower in cost and easier to use [13]. Recent studies have used a smartphone application as a colorimeter, which has proven to be a viable way to capture color for facial prostheses. However, they highlight the need for new research for image calibration, in order to increase reliability and control variables such as lighting and other environmental interferences [14]. Therefore, the present study proposes to use a smartphone to obtain photographs and develop a digital calibration method to increase the reliability of obtaining the real color, in order to improve color reproducibility in facial prostheses.

Methods
This study was carried out at the Dentistry Clinic of Paulista

Lighting and Ambience
Ambient light, inside the clinic, was guaranteed only by nonincident natural lighting directly on the patient's face, with the face illuminated naturally, without any exacerbated brightness. The patient was positioned in front of a white surface, as a bachground, without any markings, with the face turned directly toward the camera.

Standardization
The glow of the photographs was standardized using two

Photographic Shots
Photographic shots of each patient were taken using a Samsung Galaxy S8+ smartphone, Seoul, South Korea in automatic mode and flash on, to minimize environmental interferences. The  The first two referred to "calibrated photographs" and the last two referred to "original photographs." Each group had five points, i.e., 5 L*a*b* coordinates.

Calculating the Difference in Tonality
For the calculation of numerical difference in tonality between the colors obtained, the formula of difference in tonality was applied [15]: The L*a*b values of each point and their respective symmetrical correspondents were inserted into the formula, so that at the end of the calculation the ΔE value was obtained, which is equivalent to the numerical difference between the two tonalities. The first calculation was between the Pw/oC and PwC groups, aiming to evaluate the color variation before and after calibration on the patient's prosthesis. The next groups to be submitted to the tonality difference formula were Ew/oC and EwC, to evaluate the variation in the patient's skin tone before and after calibration. Groups of the same photograph were also compared; the Pw/oC and Ew/oC groups, and the PwC and EwC groups.

Statistical Analysis
The intra class correlation test (ICC) was applied to verify concordance between photos before calibrating and after calibration. Posteriorly, the t-Student test for paired samples was applied, with the aim of verifying difference in the averages of the parameters studied before and after calibration. Was the statistical program SPSS 2.1 was used, adopting α = 0.05.

Results
For the analysis of concordance between the points collected without calibration and after calibration, the intraclass agreement test was applied to the points without calibration and after calibration, as shown in Table 1. The collection of points from the five different regions, both on the prosthesis and on the eyelid (inner edge, outer edge, lower edge, most superficial, and deepest point) resulted in 30 measurements. The result of the intra class correlation showed a correlation between the parameters analyzed in the groups (p < 0.05). The L*, a*, and b* parameters for the prosthesis in the photographs before calibration and after calibration were considered adequate (ICC < 0.75), demonstrating that they are comparable. An adequate ICC in the eye region was also found for the L* and a* parameters, with ICC = 0.910 and 0.960, respectively (p < 0.05). For the b* parameter, the ICC was 0.67, which is considered moderate, but significant. After the analysis of concordance, the parametric test was applied to compare paired Student t mean values. The results are shown in Table 2  before calibration. However, no significant differences were observed in the b* parameter when comparing before and after calibration.
Graph 1: Average color.  Note: *Indicates a statistically significant difference between the groups compared.

Discussion
The smartphone has recently been used in studies in the area of facial prostheses to reproduce the facial anatomy through photogrammetry and texture maps, seeking to refine the definition of the patient's skin [11,12]. The smartphone has also been used as a colorimeter in color studies in facial prosthesis, but there is a need to increase the reliability of methods for obtaining color through the cameras of these devices [14]. Staining is one of the most complex stages in the manufacture of facial prostheses, as small changes in tonality can be perceived by the human eye, which has the same ability to identify colors as colorimeters and spectrophotometers, so that even minimal differences in tonality between the skin and the prosthetics are noticeable to the patients and to those around them [16]. Thus, considering that the smartphone is a versatile tool, with potential use in the manufacture of facial prostheses, this study aimed to find alternative ways to enable its use in obtaining and standardizing colors. Previous research has shown that various environmental factors, such as lighting, skin brightness, shadows, and camera configuration, generate interference and modify the accuracy of the photographs obtained [14]. To control these factors, the present study uses a 3-step method of calibration of the  however, reproducing real color is one of the greatest challenges for the effective production of this fully printed 3D prosthesis. This fact reinforces the importance of this study in the context of calibration and standardization of colors [15]. With the methodology proposed in this study, the calibration of photographs with a simple reference element can allow the professional to use any model of smartphone without having to use complex camera settings, but only automatic mode given that standardization with filters and calibration can ensure the authenticity of the colors. In contrast to expensive spectrophotometry equipment, the smartphone is a simple and affordable resource that is easy to handle, and is already used for different functions in the production of facial prostheses. Based on the method of standardization and calibration of photographs proposed in this study, its use can be expanded, taking another step toward the production of a fully digital prosthesis. New studies are needed to put this methodology to the test, evaluating variations in skin tones and the accuracy of obtaining silicone samples compatible with the colors obtained from the patient's skin through this technique. In natural evolution of knowledge and 3D printing technology, with silicone printers of the future after defining the patient's actual skin tone using a smartphone, it will be possible to print a prosthesis without the need for retouching by a human hand. However, even before such silicone printing capabilities are developed, it will be possible to use this technique to define actual skin color and compare with silicone samples developed by prosthesis specialists, with a higher degree of precision, reducing working time, and the need for costly equipment.
Within the limitations of the small sample size of this study, the results show that standardization of photographs using polarized light filters, and calibration of colors using a reference element, enable the use of the smartphone as a tool for obtaining and defining colors for the production of facial prostheses. Future studies with a higher number of samples are needed to prove our results.
Comparison between the pre-and post-calibration photographs showed statistically significant difference, demonstrating that without standardization or calibration, the smartphone is not a reliable tool for color definition; its use being restricted to documenting of cases, but not extending to the production of prostheses. The proposed technique, which includes the usage of smartphones, provides a reliable and accessible workflow to assist the specialist to obtain calibrated digital photography to register different regions of the facial skin and facial prosthesis. Reduced discrepancies between the real color of a face and the output file of a digital photography is an important tool for quality control, as well as in manufacturing process. In the near future, when digital workflows of Color 3D Printing may be predictable to transform smartphone captures up to the final colored 3D prosthesis, color calibration will be one of the most important steps for an accurate fabrication.

Conclusion
The results showed that with the proposed standardization