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A hybrid color space for skin detection using genetic algorithm heuristic search and principal component analysis technique

Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space...

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Main Authors: Oghaz, Mahdi Maktabdar, Maarof, Mohd. Aizaini, Zainal, Anazida, Rohani, Mohd. Foad, Yaghoubyan, S. Hadi
Format: Article
Published: Public Library of Science 2015
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/id/eprint/55468/
http://dx.doi.org/ 10.1371/journal.pone.0134828
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spelling my.utm.554682017-08-08T08:20:41Z http://eprints.utm.my/id/eprint/55468/ A hybrid color space for skin detection using genetic algorithm heuristic search and principal component analysis technique Oghaz, Mahdi Maktabdar Maarof, Mohd. Aizaini Zainal, Anazida Rohani, Mohd. Foad Yaghoubyan, S. Hadi QA75 Electronic computers. Computer science Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space in terms of skin and face classification performance which can address issues like illumination variations, various camera characteristics and diversity in skin color tones has remained an open issue. This research proposes a new three-dimensional hybrid color space termed SKN by employing the Genetic Algorithm heuristic and Principal Component Analysis to find the optimal representation of human skin color in over seventeen existing color spaces. Genetic Algorithm heuristic is used to find the optimal color component combination setup in terms of skin detection accuracy while the Principal Component Analysis projects the optimal Genetic Algorithm solution to a less complex dimension. Pixel wise skin detection was used to evaluate the performance of the proposed color space. We have employed four classifiers including Random Forest, Naïve Bayes, Support Vector Machine and Multilayer Perceptron in order to generate the human skin color predictive model. The proposed color space was compared to some existing color spaces and shows superior results in terms of pixel-wise skin detection accuracy. Experimental results show that by using Random Forest classifier, the proposed SKN color space obtained an average F-score and True Positive Rate of 0.953 and False Positive Rate of 0.0482 which outperformed the existing color spaces in terms of pixel wise skin detection accuracy. The results also indicate that among the classifiers used in this study, Random Forest is the most suitable classifier for pixel wise skin detection applications. Public Library of Science 2015-08 Article PeerReviewed Oghaz, Mahdi Maktabdar and Maarof, Mohd. Aizaini and Zainal, Anazida and Rohani, Mohd. Foad and Yaghoubyan, S. Hadi (2015) A hybrid color space for skin detection using genetic algorithm heuristic search and principal component analysis technique. PLoS ONE, 10 (8). ISSN 1932-6203 http://dx.doi.org/ 10.1371/journal.pone.0134828 DOI: 10.1371/journal.pone.0134828
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Oghaz, Mahdi Maktabdar
Maarof, Mohd. Aizaini
Zainal, Anazida
Rohani, Mohd. Foad
Yaghoubyan, S. Hadi
A hybrid color space for skin detection using genetic algorithm heuristic search and principal component analysis technique
description Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space in terms of skin and face classification performance which can address issues like illumination variations, various camera characteristics and diversity in skin color tones has remained an open issue. This research proposes a new three-dimensional hybrid color space termed SKN by employing the Genetic Algorithm heuristic and Principal Component Analysis to find the optimal representation of human skin color in over seventeen existing color spaces. Genetic Algorithm heuristic is used to find the optimal color component combination setup in terms of skin detection accuracy while the Principal Component Analysis projects the optimal Genetic Algorithm solution to a less complex dimension. Pixel wise skin detection was used to evaluate the performance of the proposed color space. We have employed four classifiers including Random Forest, Naïve Bayes, Support Vector Machine and Multilayer Perceptron in order to generate the human skin color predictive model. The proposed color space was compared to some existing color spaces and shows superior results in terms of pixel-wise skin detection accuracy. Experimental results show that by using Random Forest classifier, the proposed SKN color space obtained an average F-score and True Positive Rate of 0.953 and False Positive Rate of 0.0482 which outperformed the existing color spaces in terms of pixel wise skin detection accuracy. The results also indicate that among the classifiers used in this study, Random Forest is the most suitable classifier for pixel wise skin detection applications.
format Article
author Oghaz, Mahdi Maktabdar
Maarof, Mohd. Aizaini
Zainal, Anazida
Rohani, Mohd. Foad
Yaghoubyan, S. Hadi
author_facet Oghaz, Mahdi Maktabdar
Maarof, Mohd. Aizaini
Zainal, Anazida
Rohani, Mohd. Foad
Yaghoubyan, S. Hadi
author_sort Oghaz, Mahdi Maktabdar
title A hybrid color space for skin detection using genetic algorithm heuristic search and principal component analysis technique
title_short A hybrid color space for skin detection using genetic algorithm heuristic search and principal component analysis technique
title_full A hybrid color space for skin detection using genetic algorithm heuristic search and principal component analysis technique
title_fullStr A hybrid color space for skin detection using genetic algorithm heuristic search and principal component analysis technique
title_full_unstemmed A hybrid color space for skin detection using genetic algorithm heuristic search and principal component analysis technique
title_sort hybrid color space for skin detection using genetic algorithm heuristic search and principal component analysis technique
publisher Public Library of Science
publishDate 2015
url http://eprints.utm.my/id/eprint/55468/
http://dx.doi.org/ 10.1371/journal.pone.0134828
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score 13.211869

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