A fusion approach for efficient human skin detection

A reliable human skin detection method that is adaptable to different human skin colors and illumination conditions is essential for better human skin segmentation. Even though different human skin-color detection solutions have been successfully applied, they are prone to false skin detection and a...

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Main Authors: Tan, W.R., Chan, C.S., Yogarajah, P., Condell, J.
Format: Article
Published: 2012
Subjects:
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author Tan, W.R.
Chan, C.S.
Yogarajah, P.
Condell, J.
author_facet Tan, W.R.
Chan, C.S.
Yogarajah, P.
Condell, J.
author_sort Tan, W.R.
collection UM
description A reliable human skin detection method that is adaptable to different human skin colors and illumination conditions is essential for better human skin segmentation. Even though different human skin-color detection solutions have been successfully applied, they are prone to false skin detection and are not able to cope with the variety of human skin colors across different ethnic. Moreover, existing methods require high computational cost. In this paper, we propose a novel human skin detection approach that combines a smoothed 2-D histogram and Gaussian model, for automatic human skin detection in color image(s). In our approach, an eye detector is used to refine the skin model for a specific person. The proposed approach reduces computational costs as no training is required, and it improves the accuracy of skin detection despite wide variation in ethnicity and illumination. To the best of our knowledge, this is the first method to employ fusion strategy for this purpose. Qualitative and quantitative results on three standard public datasets and a comparison with state-of-the-art methods have shown the effectiveness and robustness of the proposed approach.
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spelling um.eprints-55592013-04-16T01:26:26Z http://eprints.um.edu.my/5559/ A fusion approach for efficient human skin detection Tan, W.R. Chan, C.S. Yogarajah, P. Condell, J. T Technology (General) A reliable human skin detection method that is adaptable to different human skin colors and illumination conditions is essential for better human skin segmentation. Even though different human skin-color detection solutions have been successfully applied, they are prone to false skin detection and are not able to cope with the variety of human skin colors across different ethnic. Moreover, existing methods require high computational cost. In this paper, we propose a novel human skin detection approach that combines a smoothed 2-D histogram and Gaussian model, for automatic human skin detection in color image(s). In our approach, an eye detector is used to refine the skin model for a specific person. The proposed approach reduces computational costs as no training is required, and it improves the accuracy of skin detection despite wide variation in ethnicity and illumination. To the best of our knowledge, this is the first method to employ fusion strategy for this purpose. Qualitative and quantitative results on three standard public datasets and a comparison with state-of-the-art methods have shown the effectiveness and robustness of the proposed approach. 2012 Article PeerReviewed Tan, W.R. and Chan, C.S. and Yogarajah, P. and Condell, J. (2012) A fusion approach for efficient human skin detection. IEEE Transactions on Industrial Informatics, 8 (1). pp. 138-147. ISSN 1551-3203, http://ieeexplore.ieee.org/ielx5/9424/6133473/06051482.pdf?tp=&arnumber=6051482&isnumber=6133473
spellingShingle T Technology (General)
Tan, W.R.
Chan, C.S.
Yogarajah, P.
Condell, J.
A fusion approach for efficient human skin detection
title A fusion approach for efficient human skin detection
title_full A fusion approach for efficient human skin detection
title_fullStr A fusion approach for efficient human skin detection
title_full_unstemmed A fusion approach for efficient human skin detection
title_short A fusion approach for efficient human skin detection
title_sort fusion approach for efficient human skin detection
topic T Technology (General)
work_keys_str_mv AT tanwr afusionapproachforefficienthumanskindetection
AT chancs afusionapproachforefficienthumanskindetection
AT yogarajahp afusionapproachforefficienthumanskindetection
AT condellj afusionapproachforefficienthumanskindetection
AT tanwr fusionapproachforefficienthumanskindetection
AT chancs fusionapproachforefficienthumanskindetection
AT yogarajahp fusionapproachforefficienthumanskindetection
AT condellj fusionapproachforefficienthumanskindetection