## 4 Tests
As a summary we can conclude that the size of the regions varies between 26% and 28% of the size of the ideal area depending on the number of regions. Figure 9: Number of correspondences (closer centroids) between each ideal centroid and the real ones (**a**). Standard deviation and average distance from the centroid to the geometrical center of the regions (**b**). The average distance between the geometrical centers of the regions and the centroids representing them is shown in Figure 9. These distances go from 4% to 2% of the side of the ideal region with a coefficient of variation between 3% and 2%. According to this, the biggest average distance between a centroid and its correspondent is 6.67% of the side of the ideal region, a difference that is not appreciable in a visual examination of the results. This is due to the uniformity of the illumination inside the regions, as there are not big artifacts that are kept inside a region. As the region gets smaller, the probability of finding big differences in the luminance inside it, decreases. The average color and standard deviation in a 0-256 scale for each channel are shown in Figure 10. From these data we can conclude that the amount of green is around three times the amount of red and four times the amount of blue, being a good configuration for the chroma-keying technique (as one of the channels stands out from the other two). The coefficient of variation is under 4% for the red, under 2% for the blue and under 8% for the green, as the green is the dominant color. After this analysis, the illumination was modified by considering that the luminance should increase in both sides of the cyclorama to match the amount light in the center. The new configuration was verified by an expert using the traditional photometer procedure, confirming the validity of the information obtained through the proposed calibration process to detect and correct light variations in the cyclorama. Then, a second iteration of the calibration process was performed in order to check the improvements in the results and set a data reference from an illumination validated by an expert. An example of the resulting images is presented in Figure 8b. Visually, the results show an improvement in the uniformity of the regions yet keeping a difference between the regions on both sides and the regions in the center. From the point of view of the centroid correspondence (Figure 9), the results are similar. Thus, a third iteration of the process was performed. Some visual results are presented in Figure 8c. As it can be noted in these images, the uniformity of the regions has increased, and the number of free centroids or centroids with more than one correspondence has decreased to under 10% in all cases (Figure 9). Statistically, an improvement of between 5% and 8%, depending on the number of regions, is achieved. As it is shown in Figure 10, the coefficient of variation of the area of the regions goes from 14.3% for 64 regions to 16.3% for 1024 regions. This supposes an improvement of more than the 10% with respect to the original worn out configuration. The average distance between the geometrical centers of the regions and the centroids representing them (Figure 9) was reduced to under 2% in all cases but the 64 regions configuration (2.45%). The coefficient of variation is kept under 1.5% in all cases with the exception of the one with 64 subdivisions, in which it reaches 1.9%. The average color and coefficient of variation do not show noticeable changes, as the proportions between the different colors are maintained. Finally, the lights were recalibrated again, and a fourth iteration was performed, but it did not show any significant improvement, probably due to the number and quality of lights in the set, which did not allow a better configuration.