## 3 Results and Discussions
### Effect of the Light Source and the White Balance Function  
The evaluation of the impact of the light source and the application of a white balance function on the RGB intensity values was undertaken across different axial loadings. In this process, two different types of light sources were assessed, and an additional variable introduced was the use or non-use of the auto white balance function. These different scenarios yielded a varied range of RGB value distributions, which are clearly visualized in Figures 15-17.  
Figure 14: Interquartile ranges of the RGB values for the photoelastic particles with different types of adhesives: (**a**) R-value; (**b**) G-value; (**c**) B-value.  
Figure 15: R-value distribution of the photoelastic particles at various loading levels: (**a**) white light, AWB; (**b**) white light, NWB; (**c**) RGB LED, AWB; (**d**) RGB LED, NWB (AWB = auto white balance, NWB = non-white balance).  
Figure 16: G-value distribution of the photoelastic particles at various loading levels: (**a**) white light, AWB; (**b**) white light, NWB; (**c**) RGB LED, AWB; (**d**) RGB LED, NWB (AWB = auto white balance, NWB = non-white balance).  
Figure 17: B-value distribution of the photoelastic particles at various loading levels: (**a**) white light, AWB; (**b**) white light, NWB; (**c**) RGB LED, AWB; (**d**) RGB LED, NWB (AWB = auto white balance, NWB = non-white balance).  
In particular, the R value presented a unique pattern. Upon application of a load exceeding 200 N, the R value intensity initially decreased before increasing again. This pattern was noticeably different from the B and G value responses. These values reached their maximum at lower load levels compared to the R values. Despite this difference in individual responses, the overall RGB value patterns maintained a similar sine wave-like pattern. This was especially noticeable at load levels of 300 N or higher. At these load levels, the waveform amplitude decreased, causing minimal changes in the RGB values.  
Figure 18 offers another perspective by representing the median values extracted from the data sets depicted in Figures 15-17. An interesting observation from this data was that the distribution of the R values demonstrated a greater degree of variability based on experimental conditions compared to the G and B values. This variability was even more pronounced in Cases 5 and 6. These cases, which employed white light as the source, exhibited greater R value intensities than those observed in Cases 7 and 8, which utilized the RGB LED as the light source.  
The use of the white balance function also had a substantial influence on the R values. When used under white light, which is classified as a colder temperature light at 9259 K, the R value was significantly adjusted. This adjustment was also observed in Cases 7 and 8. Here, the RGB LED, having a cooler color temperature of 9641 K compared to white light, also led to a greater adjustment of the R value when the white balance function was applied.  
Finally, the interquartile range of the data sets, summarized in Figure 19, provided an important observation. Cases 5 to 8 demonstrated similar interquartile ranges, without any large difference. As these experiments were conducted on the same soil particle model, the consistency of the photoelastic response seemed to remain largely unaffected by the light source and the digital camera's white balance function. This observation underscores the fact that the variability in the results stemmed mainly from the differences in the adhesives used in creating the model particles and not from these other factors.  
Figure 19: Interquartile ranges of the RGB values for the photoelastic particles with different light sources and the white balance function: (**a**) R-value; (**b**) G-value; (**c**) B-value.  
Figure 18: Comparison of the RGB value distribution for the four cases: (**a**) R-value; (**b**) G-value; (**c**) B-value.