IEEE Transactions on Consumer Electronics Authors: Hyun-Chul Do, Ju-Yeon You, and Sung-Il Chien

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Skin Color Detection through Estimation and Conversion

of Illuminant Color Under Various Illuminations

IEEE Transactions on Consumer Electronics

Authors: Hyun-Chul Do, Ju-Yeon You, and Sung-Il Chien

Speaker:吳昱慧Date:2010/03/23

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Outline• Introduction

• Skin color detection through estimation and conversion of illuminant color

• Experimental results and discussion

• Conclusion

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Introduction

• Size invariant and facilitates • Skin color in image applications

– Image content filtering– Content-aware video compression

• HSV color space is closer to the humen perception

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Introduction

• Uses a static model in image under various illumination conditions

• Robust skin color detection considering the illumination conditions

• Can then be detected using the skin locus and adaptive histogram backprojection

• For more effective estimation of the illuminant color

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Skin color detection through estimation and conversion of illuminant color

Gamma corrected input image

Extraction of eye region candidates

Inverse gamma correction

Selection of the best pair of eyes

Extraction of sclera of the eye

Estimation of illuminant color

Canonical illuminant

Eye region template

Knowledge based rules

RiGiBi to XiYiZi conversion

XcYcZc to RcGcBc conversion

Gamma correction

Skin color detection using HSV color

Space

Skin color detected image

Conversion matrix calculation

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Skin color detection through estimation and conversion of illuminant color

A. Illuminant color estimation using sclera• The eye detection is performed for segmentin

g the sclera region in an image• Traditional eye dection methods can be classi

fied into three categories– Template-based methods– Appearance-based methods– Feature-based methods

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Skin color detection through estimation and conversion of illuminant color• Eye detection in a complex image is very

difficult• Eye detection can be simply and efficiently

implemented for frontal face images • Edge-based template matching and

knowledge-based rules

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Skin color detection through estimation and conversion of illuminant color• Pupil has a low intensity the sclera has a high

intensity

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Skin color detection through estimation and conversion of illuminant color• Candidates are selected using the eye template

and the edge of the input image• Is carried out in the frequency domain via FFT

2

),(

),(

1

),(1

),(1

)/()(tan

sin

i

i

i

Ayxi

ii

Ayxii

jjiij

jijiijij

EyxYA

yxYA

E

xxyywhere

EED

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Skin color detection through estimation and conversion of illuminant color• Finally estimated by averaging the

values within the segmented sclera region

BGR

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Skin color detection through estimation and conversion of illuminant color

B. Skin color detection through illuminant color conversion

yxzZYX

YyZYX

Xx

1,,

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Skin color detection through estimation and conversion of illuminant color• Assumed that the estimated and target luminan

ce values remain the same that is﹐ ﹐1

e

tY

Y

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Skin color detection through estimation and conversion of illuminant color• Hue(H) ﹕spectral composition • Saturation(S) ﹕refer to the purity• Value(V) ﹕brightness

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Experimental results and discussion

• Four types of illumination– Horizon sunlight (incandescent, 2300K; marked

“H”)– Incandescent A (CIE A, 2856K; marked “A”)– Fluorescent TL84 (4000K; marked “T”)– Daylight source (CIE D65, 6500K; marked “D”)

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Experimental results and discussion

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Experimental results and discussion

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Experimental results and discussion

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Conclusion

• Estimated using the pixels of the sclera region that are segmented from the eyes in face images

• Face detection and skin color enhancement even under changing illumination