mathematical model of skin color for face detection

Mathematical Model of Skin

Color for Face Detection

Setiawan Hadi, Adang Suwandi A,

Iping Supriana S, Farid Wazdi

Universitas Padjadjaran, Bandung, Indonesia

Institut Teknologi Bandung, Indonesia

Introduction

• Face detection is a preprocessing step of facial recognition system (Essential)

Introduction

• Goal: localize face(s) in digital image and/or in real time video

Skin-based Face Detection

• Skin important element in detecting image that contain skin or skin-like region

• Skin is special

– covers most of the face image area

– skin of different people appears to vary over a wide

range, however the differ is much less in colour

(chromaticity) than brightness

– detection of skin area in digital image are more

practical and easy to implement.

Our Research Approach

• Skin colour is represented in 3 colour space (rg, HSB and YCbCr)

• Using mathematical model that is generated from face images

• Implement morphological filters for enhancing face image

• Apply 4-neigbourhood ellipse representation for localizing face

• Using local face databases for experiment

Face in Colour Spaces RGB space

HSB space

YCbCr space

Generating Face Skin Model

• Calculate mean and covariance chromaticity of training images for each colour space

• Training images are prepared semi-manually

M k =

n X

i = 1

1

± i T i

M k = 1

± 1

T 1 + 1

± 2

T 2 + ¢ ¢ ¢ + 1

± n ¡ 1

T n ¡ 1 + 1

± n

T n

Sample of generated skin colour model

Skin distribution in Colour Spaces

Face Detection

Algorithm

w h e r e P s k i n ( i ; j ) i s p r o b a b i l i t y o f

p i x e l P a s s k i n p i x e l i f i n c l u d e d

i n d i s t r i b u t i o n s k i n m o d e l D M k

f o r e v e r y c o l o u r s p a c e s R n .

P s k i n ( i ; j ) = P s k i n ( i ; j ) 2 D M k 8 P ( i ; j ) ^ 8 R n

Visual Result

Experiments

Concluding remarks

• Skin colour is modelled using using mean-covariance characteristics

• Skin colour is represented in 3 colour space

• Skin model is used for face detection, with support morphological filter dan 4-neigborhood ellipse generation

• Experiment has been performed using 7 sets of face database, >>3000 face images

• Accuracy needs to be improved

Next Work

• Multiple image detection

• Symmetry and features detection

• Adding geometric-based detection to increase detection accuracy

• Algorithm improvement for efficient yet faster detection

• Realtime face detection

• Face recognition module

Mathematical Model of Skin

Color for Face Detection

Setiawan Hadi, Adang Suwandi A,

Iping Supriana S, Farid Wazdi

Universitas Padjadjaran, Bandung, Indonesia

Institut Teknologi Bandung, Indonesia