Skin Segmentation

Donated on 7/16/2012

The Skin Segmentation dataset is constructed over B, G, R color space. Skin and Nonskin dataset is generated using skin textures from face images of diversity of age, gender, and race people.

Dataset Characteristics


Subject Area

Computer Science

Associated Tasks


Feature Type


# Instances


# Features


Dataset Information

Additional Information

The skin dataset is collected by randomly sampling B,G,R values from face images of various age groups (young, middle, and old), race groups (white, black, and asian), and genders obtained from FERET database and PAL database. Total learning sample size is 245057; out of which 50859 is the skin samples and 194198 is non-skin samples. Color FERET Image Database:, PAL Face Database from Productive Aging Laboratory, The University of Texas at Dallas:

Has Missing Values?


Variables Table

Variable NameRoleTypeDescriptionUnitsMissing Values

0 to 4 of 4

Additional Variable Information

This dataset is of the dimension 245057 * 4 where first three columns are B,G,R (x1,x2, and x3 features) values and fourth column is of the class labels (decision variable y).

Papers Citing this Dataset

Driver Distraction Identification with an Ensemble of Convolutional Neural Networks

By Hesham Eraqi, Yehya Abouelnaga, Mohamed Saad, Mohamed Moustafa. 2019

Published in Journal of Advanced Transportation, Machine Learning in Transportation (MLT) Issue, 2019.

Nonparametric feature extraction based on Minimax distance

By Morteza Chehreghani. 2019

Published in ArXiv.

Case-Based Reasoning: The Search for Similar Solutions and Identification of Outliers

By Piotr Szczepaniak, Agnieszka Duraj. 2018

Published in Complexity.

Distributed query-aware quantization for high-dimensional similarity searches

By Gheorghi Guzun, Guadalupe Canahuate. 2018

Published in Advances in database technology : proceedings. International Conference on Extending Database Technology.

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10 citations


Rajen Bhatt

Abhinav Dhall


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