# Facial Recognition Method Based on Thin-Film Solar Cells
## 3 Results and Discussion  
After the facial recognition system was established, it was tested with six testers. The photographs of the six testers demonstrated different characteristics in terms of hair length, skin color, and facial contour. The system's ability to identify differences among the acquired data and correlate them with the features in the photographs is critical to its success as a facial recognition system. For a detailed investigation, we also conducted 3D contour scanning for the testers using an iPhone 12 Pro and Bellus3D FaceApp (Figures 6-11).  
Figure 4: White light spectra of the left and right LED light strips.  
Figure 5: Comparisons of six consecutive sets of test data.  
Figure 8: (**a**) Tester 3 and (**b**) his side-view 3D scan image.  
Figure 6: Tester 1 (**a**) and his side-view 3D scan image (**b**).  
Figure 7: Tester 2 (**a**) and her side-view 3D scan image (**b**).  
Figure 9: (**a**) Tester 4 and (**b**) his side-view 3D scan image.  
To avoid plotting the data for all testers on the same graph, we chose Tester 1 as a reference to separately compare his data with the others. The facial areas corresponding to the solar cells are demonstrated in Figure 12. SC01-SC04 correspond to the forehead, SC05-SC08 correspond to the eyes, cheeks, and nose, and SC9-SC12 correspond to the mouth and chin.  
Figure 12 illustrates that the Tester 2 voltage values of SC01, SC04, SC05, and SC08 are lower than those of Tester 1, which is affected by hair. The facial areas of Tester 2 corresponding to SC05 and SC08 (the cheeks) are covered by hair, resulting in lower voltages values. For Tester 1, the value of SC04 is higher than that of SC01 because of a slanted fringe. The exposed forehead area corresponding to SC04 is larger, so the reflected light of LED illumination entering the thin-film solar cell has higher intensity, and the voltage value is higher.  
Figure 11: (**a**) Tester 6 and (**b**) his side-view 3D scan image.  
Figure 10: (**a**) Tester 5 and (**b**) his side-view 3D scan image.  
The differences in the values of SC01-SC04 corresponding to the forehead are significant because of the differences in the testers' hairstyles (Figure 16). For SC06 and SC07, we can observe from the 3D scan images that the facial areas on both sides of the nose of Tester 5 are raised, whereas the same areas of Tester 1 are flat. A flat surface favors light reflection, but a raised surface generates diffused reflection, and hence, reduced intensity of the light entering the sensing element. Therefore, the Tester 5 SC06 and SC07 data are lower than those of Tester 1.  
The photographs indicate that the face of Tester 6 is rounder. Therefore, the of SC05 and SC08 values for Tester 6 are higher than those of Tester 1 (Figure 17). In addition, the skin color of Tester 6 is lighter, so the overall data values of Tester 6 are also higher. The 3D model of Tester 6 shows that facial areas on both sides of the nose are slightly raised, indicated by the shallows. The reflected diffusion decreases the intensity of the light  
Figure 16: Differences between the Tester 1 and Tester 5 data.  
Figure 15: Differences between the Tester 1 and Tester 4 data.  
entering the sensing element, so the Tester 6 voltage values of SC06 and SC07 are lower than those of Tester 1.  
Although we successfully identified six different testers, the SC05-SC08 values of several testers were similar, which may be limited by small voltage changes of the solar cell in high-light environment. Ideally, current variations in high-light environments should also be detected; however, a micro-current detection element suitable for the Arduino MEGA2560 has not been found. If we can divide the voltage records of each solar cell in our present system into eight intervals, then the array with 12 solar cells will generate 8 to the 12 th power of possibilities (812).