Our hypothesis was that our skin tones are not that much different than we recognize. So we started this project to detect the average skin tone of participants and put those tones on the color table. Through this we can see how different our skin colors are visually and objectively. We tested around 50 students, and these in return have made a small cluster on the color table. In terms of color, we live in very small spectrum.




Basically, we used processing to place the user’s skin tone on the color table. First, users will see the current cluster of average skin color tone at the first screen. Second, users will place enough facial skin to be exposed, and a picture will be taken. Third, users will choose a few data points that he/she thinks is his/her skin tone. Fourth, the average skin tone will be displayed with RGB values. Finally, the users’ average skin color will be placed on the color table that was first seen at the start. < br />



At the user test of 50 students, 3 outliers have been detected. We think the outliers are outliers because of the light! Lighting is a very important factor in this project. Once the stable light and stable environment have been set up, the result will be very solid. Every time the data is saved, we hope people re-think about the history of discrimination.