## 3 Results
### The Effect of Cutting Was Studied by Photographic Color Extraction
#### 3.3.1 Color Concentration Improvement  
On the one hand, the cutting directly affects the color of the gem by changing the bottom angle of the gem to concentrate on light. On the other hand, the fire colors caused by the small facet's reflection also affect the gem color. By sticking the gem onto plasticine, it changes the appearance of the fire color (The sticky plasticine makes the bottom small facet unreflective). This paper studies the effect of the fire color on the gem color, by comparing the presence of sticky plasticine. Then we study the direct impact of cutting on the color of the gem (excluding the influence of the fire color). Three forms were selected for the photo, the first is the obverse side photographed, that is stuck to the plasticine, the second is photographed reverse side up to the plasticine and the third is photographed on the white cushions (Figure 9). And we tested 35 samples in three ways, as shown in Figure 10.  
In this study, we divide the cuttings into two parts. One is the \"overall cutting\", by sharpening the bottom of the stone (by comparing the obverse and reverse of a stone without the fire color), and the other is the \"small facet cutting\" (by comparing the obverse of a gem with or without the fire color). The overall cutting has a major impact on the color change. By sharpening the bottom of the gem, the total reflection of light occurs and the luminous flux inside the gem increases. On the one hand, the increase of the light path makes more chromogenic ions release energy; on the other hand, the total reflection reduces the loss of light, which is equivalent to the increase of the light intensity. To stimulate more chromogenic ions to release energy, they can make the stone have a greater color saturation. We compare the color change on the obverse and reverse sides of a stone without the fire color, that is, we study the impact of the overall cutting on the color. The average absolute values of C and L changes are 6.16 and 6.27. The change in h is very small, only 1.11, so we will not discuss further. The average color difference before and after cutting is 9.53, which means that there is an obvious color difference that can be distinguished by the naked eye. To judge whether the color is improved after cutting, we can see from the grading chart (Figure 11) that the larger the C value; the smaller the L value in this range  
Figure 10: Three kinds of photos of 35 samples are: the obverse side with the fire color, the obverse side without the fire color and the reverse side without the fire color. Figure 9: (**Left**) the obverse and reverse of a stone without the fire color (both stuck to the plasticine); (**Right**) the obverse of a gem with or without the fire color (stuck to the plasticine and placed on the white cushion). (L is in the range of 30-60), the better the color. Following cutting, 88.57% of the gems' L decreases (6 of gems are lower than 30), so 71.43% of the gems' L* plays an optimization role, and 77.14% of the gems' C* increases. Six gems' L and C were not optimized after cutting, six samples' L or C were optimized, and 23 gems' L and C were both optimized (Table 1). Comparing the obverse side of a gem with or without the fire color, the average color difference can be obtained by comparing the influence of the small facet (fire color) on the color with or without the paste. The color difference \(\Delta\)E = 6.93 is also an obvious color difference that can be distinguished by the naked eye. The average value of L* change is 4.41, the average value of C* change is 4.56 and the average value of h change is 1.46. There are 19 gems' L* that decrease after cutting (three gems are lower than 30), so 16 gems' L* are optimized. Sixteen gems' C increase after cutting. Five samples were optimized for both parameters (L* and C*)(Isa-6, Isa-21, Isa-30, Isa-33, Isa-35), eight samples were not optimized for both parameters (Tsa-2, Tsa-4, Tsa-5, Tsa-10, Isa-16, Isa-17, Isa-19, Isa-20), and the other 16 samples were optimized for one parameter (L* or C*) (Table 1).