Color space selection for human skin detection using color-texture features and neural networks

Hani K. Al-Mohair; Junita Mohamad-Saleh; Shahrel Azmin Suandi

doi:10.1109/ICCOINS.2014.6868362

Color space selection for human skin detection using color-texture features and neural networks

Hani K. Al-Mohair
, Junita Mohamad-Saleh
, Shahrel Azmin Suandi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Scopus citations

Abstract

Skin color is a robust cue in human skin detection. It has been widely used in various human-related image processing applications. Although many researches have been carried out for skin color detection, there is no consensus on which color space is the most appropriate for skin color detection because many researchers do not provide strict justification of their color space choice. In this paper, a comprehensive comparative study using the Multilayer Perceptron artificial neural network (MLP), which is a universal classifier, is carried out to evaluate the overall performance of different color-spaces for skin detection. It aims at determining the most optimal color space using color and color-texture features separately. The study has been carried out using images of different databases. The experimental results showed that the YIQ color space gives the highest separability between skin and non-skin pixels among the different color spaces tested using color featuResearch Combining color and texture eliminates the differences between color spaces but leads to much more accurate and efficient skin detection.

Original language	English
Title of host publication	2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479943913
DOIs	https://doi.org/10.1109/ICCOINS.2014.6868362
State	Published - 30 Jul 2014
Externally published	Yes

Publication series

Name	2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

Color space
Neural networks
Skin color detection
Texture analysis

ASJC Scopus subject areas

Information Systems
Environmental Engineering
Renewable Energy, Sustainability and the Environment
Computer Science Applications

Access to Document

10.1109/ICCOINS.2014.6868362

Cite this

Al-Mohair, H. K., Mohamad-Saleh, J., & Suandi, S. A. (2014). Color space selection for human skin detection using color-texture features and neural networks. In 2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings Article 6868362 (2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCOINS.2014.6868362

Al-Mohair, Hani K. ; Mohamad-Saleh, Junita ; Suandi, Shahrel Azmin. / Color space selection for human skin detection using color-texture features and neural networks. 2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. (2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings).

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abstract = "Skin color is a robust cue in human skin detection. It has been widely used in various human-related image processing applications. Although many researches have been carried out for skin color detection, there is no consensus on which color space is the most appropriate for skin color detection because many researchers do not provide strict justification of their color space choice. In this paper, a comprehensive comparative study using the Multilayer Perceptron artificial neural network (MLP), which is a universal classifier, is carried out to evaluate the overall performance of different color-spaces for skin detection. It aims at determining the most optimal color space using color and color-texture features separately. The study has been carried out using images of different databases. The experimental results showed that the YIQ color space gives the highest separability between skin and non-skin pixels among the different color spaces tested using color featuResearch Combining color and texture eliminates the differences between color spaces but leads to much more accurate and efficient skin detection.",

keywords = "Color space, Neural networks, Skin color detection, Texture analysis",

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Al-Mohair, HK, Mohamad-Saleh, J & Suandi, SA 2014, Color space selection for human skin detection using color-texture features and neural networks. in 2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings., 6868362, 2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings, Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICCOINS.2014.6868362

Color space selection for human skin detection using color-texture features and neural networks. / Al-Mohair, Hani K.; Mohamad-Saleh, Junita; Suandi, Shahrel Azmin.
2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. 6868362 (2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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PY - 2014/7/30

Y1 - 2014/7/30

N2 - Skin color is a robust cue in human skin detection. It has been widely used in various human-related image processing applications. Although many researches have been carried out for skin color detection, there is no consensus on which color space is the most appropriate for skin color detection because many researchers do not provide strict justification of their color space choice. In this paper, a comprehensive comparative study using the Multilayer Perceptron artificial neural network (MLP), which is a universal classifier, is carried out to evaluate the overall performance of different color-spaces for skin detection. It aims at determining the most optimal color space using color and color-texture features separately. The study has been carried out using images of different databases. The experimental results showed that the YIQ color space gives the highest separability between skin and non-skin pixels among the different color spaces tested using color featuResearch Combining color and texture eliminates the differences between color spaces but leads to much more accurate and efficient skin detection.

AB - Skin color is a robust cue in human skin detection. It has been widely used in various human-related image processing applications. Although many researches have been carried out for skin color detection, there is no consensus on which color space is the most appropriate for skin color detection because many researchers do not provide strict justification of their color space choice. In this paper, a comprehensive comparative study using the Multilayer Perceptron artificial neural network (MLP), which is a universal classifier, is carried out to evaluate the overall performance of different color-spaces for skin detection. It aims at determining the most optimal color space using color and color-texture features separately. The study has been carried out using images of different databases. The experimental results showed that the YIQ color space gives the highest separability between skin and non-skin pixels among the different color spaces tested using color featuResearch Combining color and texture eliminates the differences between color spaces but leads to much more accurate and efficient skin detection.

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Al-Mohair HK, Mohamad-Saleh J, Suandi SA. Color space selection for human skin detection using color-texture features and neural networks. In 2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2014. 6868362. (2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings). doi: 10.1109/ICCOINS.2014.6868362

Color space selection for human skin detection using color-texture features and neural networks

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this