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A new hybrid module for skin detector using fuzzy inference system structure and explicit rules

Skin detection is a popular image processing technique that has been applied in many areas such as video-surveillance, cyber-crime prosecution and face detection. It is also considered as one of the challenging problems in image processing. Despite being a well known technique to detect human appear...

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Main Authors: Zaidan, A.A., Karim, H.A., Ahmad, N.N., Alam, G.M., Zaidan, B.B.
Format: Article
Published: Academic Journals 2010
Subjects:
Q Science (General)
Online Access:http://eprints.um.edu.my/12142/
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spelling my.um.eprints.121422019-03-20T08:32:18Z http://eprints.um.edu.my/12142/ A new hybrid module for skin detector using fuzzy inference system structure and explicit rules Zaidan, A.A. Karim, H.A. Ahmad, N.N. Alam, G.M. Zaidan, B.B. Q Science (General) Skin detection is a popular image processing technique that has been applied in many areas such as video-surveillance, cyber-crime prosecution and face detection. It is also considered as one of the challenging problems in image processing. Despite being a well known technique to detect human appearance within image, it faces a fundamental problem when using colour as cue to detect skin. It is difficult to detect skin when the colour between the skin and the non skin within an image is similar. Therefore in this paper, a new hybrid module between explicit rules and fuzzy inference system structure, based on RGB colour space, is proposed to improve skin detection performance. Using the new hybrid module, we managed to increase the classification reliability when discriminating human skin. The new proposed skin detector depends on subtractive clustering technique, created and trained with training set of skin and non-skin pixels. The proposed system is tested on human images having upright frontal skin with any background. Our proposed system has achieved high detection rates of 87% classification and low false positives when compared with the existing methods. Academic Journals 2010 Article PeerReviewed Zaidan, A.A. and Karim, H.A. and Ahmad, N.N. and Alam, G.M. and Zaidan, B.B. (2010) A new hybrid module for skin detector using fuzzy inference system structure and explicit rules. International Journal of the Physical Sciences, 5 (13). pp. 2084-2097. ISSN 1992-1950
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic Q Science (General)
spellingShingle Q Science (General)
Zaidan, A.A.
Karim, H.A.
Ahmad, N.N.
Alam, G.M.
Zaidan, B.B.
A new hybrid module for skin detector using fuzzy inference system structure and explicit rules
description Skin detection is a popular image processing technique that has been applied in many areas such as video-surveillance, cyber-crime prosecution and face detection. It is also considered as one of the challenging problems in image processing. Despite being a well known technique to detect human appearance within image, it faces a fundamental problem when using colour as cue to detect skin. It is difficult to detect skin when the colour between the skin and the non skin within an image is similar. Therefore in this paper, a new hybrid module between explicit rules and fuzzy inference system structure, based on RGB colour space, is proposed to improve skin detection performance. Using the new hybrid module, we managed to increase the classification reliability when discriminating human skin. The new proposed skin detector depends on subtractive clustering technique, created and trained with training set of skin and non-skin pixels. The proposed system is tested on human images having upright frontal skin with any background. Our proposed system has achieved high detection rates of 87% classification and low false positives when compared with the existing methods.
format Article
author Zaidan, A.A.
Karim, H.A.
Ahmad, N.N.
Alam, G.M.
Zaidan, B.B.
author_facet Zaidan, A.A.
Karim, H.A.
Ahmad, N.N.
Alam, G.M.
Zaidan, B.B.
author_sort Zaidan, A.A.
title A new hybrid module for skin detector using fuzzy inference system structure and explicit rules
title_short A new hybrid module for skin detector using fuzzy inference system structure and explicit rules
title_full A new hybrid module for skin detector using fuzzy inference system structure and explicit rules
title_fullStr A new hybrid module for skin detector using fuzzy inference system structure and explicit rules
title_full_unstemmed A new hybrid module for skin detector using fuzzy inference system structure and explicit rules
title_sort new hybrid module for skin detector using fuzzy inference system structure and explicit rules
publisher Academic Journals
publishDate 2010
url http://eprints.um.edu.my/12142/
_version_ 1643689228650938368
score 13.211869

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