Optimum color spaces for skin detection

Albiol, Alberto; Torres, Luís; Delp, Edward J.

doi:10.1109/icip.2001.958968

Cited by 141 publications

(93 citation statements)

References 9 publications

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“…Four color spaces in conjunction with histogram based skin detection methods are evaluated in [1], claiming that skin detection performance is independent of a color space transformation that is invertible. It has been shown that RGB, YCbCr and HSV have similar performance while CbCr is different since being a 'non-invertible' color transformation.…”

Section: Related Workmentioning

confidence: 99%

Color based skin classification

Khan

Hanbury

Stöttinger

et al. 2012

Pattern Recognition Letters

133

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Skin detection is used in applications ranging from face detection, tracking body parts and hand gesture analysis, to retrieval and blocking objectionable content. In this paper, we investigate and evaluate (1) the effect of color space transformation on skin detection performance and finding the appropriate color space for skin detection, (2) the role of the illuminance component of a color space, (3) the appropriate pixel based skin color modeling technique and finally, (4) the effect of color constancy algorithms on color based skin classification. The comprehensive color space and skin color modeling evaluation will help in the selection of the best combinations for skin detection. Nine skin modeling approaches (AdaBoost, Bayesian network, J48, Multilayer Perceptron, Naive Bayesian, Random Forest, RBF network, SVM and the histogram approach of Jones and Rehg [15]) in six color spaces (IHLS, HSI, RGB, normalized RGB, YCbCr and CIELAB) with the presence or absence of the illuminance component are compared and evaluated. Moreover, the impact of five color constancy algorithms on skin detection is reported. Results on a database of 8991 images with manually annotated pixel-level ground truth show that (1) the cylindrical color spaces outperform other color spaces, (2) the absence of the illuminance component decreases performance, (3) the selection of an appropriate skin color modeling approach is important and that the tree based classifiers (Random forest, J48) are well suited to pixel based skin detection. As a best combination, the Random Forest combined with the cylindrical color spaces, while keeping the illumi- nance component outperforms other combinations, and (4) the usage of color constancy algorithms can improve skin detection performance.

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Section: Related Workmentioning

confidence: 99%

Color based skin classification

Khan

Hanbury

Stöttinger

et al. 2012

Pattern Recognition Letters

133

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“…Peu de travaux ayant été fait à ce propos (exception faite de travaux spécifiques que nous ne pouvons reprendre directement [13] [14]), nous avons développé nos propres outils afin qu'ils accordent plus d'importance aux segments de grande taille [15]. En effet, ces segments correspondent à un élément significatif de la scène et seront probablement détectés sur les deux images, prises par le système de vision stéréoscopique, conduisant ainsi à un appariement favorable.…”

Section: F Evaluationunclassified

De l'utilité de la couleur en localisation et navigation : application à un robot d'assistance

Montagne¹,

Lelandais²,

Triboulet³

2004

J3eA

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“…Albiol et al [6] show that the performance of a skin detection algorithm is largely unaffected by the color space choice, i.e. if an optimal skin detector is designed for every color space, then the performances will be same.…”

Section: Related Workmentioning

confidence: 99%

Efficient Skin Detection under Severe Illumination Changes and Shadows

Khanal

Sidibé

2011

Intelligent Robotics and Applications

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Abstract. This paper presents an efficient method for human skin color detection with a mobile platform. The proposed method is based on modeling the skin distribution in a log-chromaticity color space which shows good invariance properties to changing illumination. The method is easy to implement and can cope with the requirements of real-world tasks such as illumination variations, shadows and moving camera. Extensive experiments show the good performance of the proposed method and its robustness against abrupt changes of illumination and shadows.

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Optimum color spaces for skin detection

Cited by 141 publications

References 9 publications

Color based skin classification

Color based skin classification

De l'utilité de la couleur en localisation et navigation : application à un robot d'assistance

Efficient Skin Detection under Severe Illumination Changes and Shadows

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