Abstract

Localizing potential skin regions in a color image forms a significant step in applications like face detection, face recognition, face verification, face tracking, gesture analysis, content-based image retrieval and human computer interaction. In this study, we present a pixel based skin segmentation algorithm with ensemble approach using Gaussian Mixture Model (GMM) classifier. Skin color features are extracted using RGB, HSV, YCbCr and CIELab color spaces and ensembled into a single feature vector which is used to train the GMM classifier. Comprehensive experiments have been conducted using three different datasets, SFA Database, ECU Skin Database and UCI Skin database. The skin detection rate of our proposed classifier is observed to be better than the existing works.

Keywords:

Classifier ensemble, feature extraction , gaussian mixture model , skin segmentation,

References

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.