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
Univariate
Subject Area
Computer Science
Associated Tasks
Classification
Feature Type
Real
# Instances
245057
# Features
3
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: http://face.nist.gov/colorferet/request.html, PAL Face Database from Productive Aging Laboratory, The University of Texas at Dallas: https://pal.utdallas.edu/facedb/.
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| B | Feature | Integer | no | ||
| G | Feature | Integer | no | ||
| R | Feature | Integer | no | ||
| y | Target | Binary | no |
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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
By Hesham Eraqi, Yehya Abouelnaga, Mohamed Saad, Mohamed Moustafa. 2019
Published in Journal of Advanced Transportation, Machine Learning in Transportation (MLT) Issue, 2019.
By Morteza Chehreghani. 2019
Published in ArXiv.
By Sumedh Yadav, Mathis Bode. 2019
Published in ArXiv.
By Piotr Szczepaniak, Agnieszka Duraj. 2018
Published in Complexity.
By Gheorghi Guzun, Guadalupe Canahuate. 2018
Published in Advances in database technology : proceedings. International Conference on Extending Database Technology.
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset skin_segmentation = fetch_ucirepo(id=229) # data (as pandas dataframes) X = skin_segmentation.data.features y = skin_segmentation.data.targets # metadata print(skin_segmentation.metadata) # variable information print(skin_segmentation.variables)
Bhatt,Rajen and Dhall,Abhinav. (2012). Skin Segmentation. UCI Machine Learning Repository. https://doi.org/10.24432/C5T30C.
@misc{misc_skin_segmentation_229,
author = {Bhatt,Rajen and Dhall,Abhinav},
title = {{Skin Segmentation}},
year = {2012},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5T30C}
}Creators
Rajen Bhatt
Abhinav Dhall
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.