Face Detection and Modeling for Recognition - Biometrics Research ...

3.3.1 Eye Map
We first build two separate eye maps, one from the chrominance components and
the other from the luminance component of the color image. These two maps are
then combined into a single eye map. The eye map from the chroma is based on
the observation that high C b and low C r values are found around the eyes. It is
constructed from information contained in C b , the inverse (negative) of C r , and the
ratio C b /C r , as described in Eq. (3.1).
EyeMapC = 1 3 { (C2 b ) + ( ˜C r ) 2 + (C b /C r ) }, (3.1)
where C 2 b , ( ˜C r ) 2 , and C b /C r all are normalized to the range [0, 255] and
˜ Cr is the
negative of C r (i.e., 255 − C r ). An example of the eye map from the chroma is shown
in Fig. 3.9(a).
The eyes usually contain both dark and bright pixels in the luma component.
Based on this observation, grayscale morphological operators (e.g., dilation and erosion)
[169] can be designed to emphasize brighter and darker pixels in the luma
component around eye regions. These operations have been used to construct feature
vectors for face images at multiple scales for frontal face authentication [66].
We
use grayscale dilation and erosion with a hemispheric structuring element at a single
estimated scale to construct the eye map from the luma, as described in Eq. (3.2).
EyeMapL = Y (x, y) ⊕ g σ(x, y)
Y (x, y) ⊖ g σ (x, y) + 1 , (3.2)
where the grayscale dilation ⊕ and erosion ⊖ operations [169] on a function f : F ⊂
R 2 −→ R using a structuring function g : G ⊂ R 2 −→ R are defined as follows.
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