Rajen and Abhinav (2012) addressed the challenge of detecting skin-like regions in images as a component of the intricate process of facial recognition. To achieve this goal, they curated the “Skin segmentation” data set, comprising RGB (R-red, G-green, B-blue) values of randomly selected pixels from N = 245,057 facial images, including 50,859 skin samples and 194,198 nonskin samples, spanning diverse age groups, racial backgrounds, and genders.
Format
A data frame with 4 columns and 245,057 rows.
Skin_presenceSkin presence in the randomly selected pixels
RedRed values in the randomly selected pixels
GreenGreen values in the randomly selected pixels
BlueBlue values in the randomly selected pixels
Source
Extracted from
Rajen B, Abhinav D (2012) Skin segmentation. UCI Machine Learning Repository.
Available at: doi:10.24432/C5T30C
Examples
nrow(Skin_segmentation)
#> [1] 245057