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Automatic face detection in colored images is closely related to face recognition systems, as a preliminary critical
required step, where it is necessary to search for the precise face location. We propose a reliable approach for skin color
segmentation to detect human face in colored images under unconstrained scene conditions that overcoming the
sensitivity to the variation in face size, pose, location, lighting conditions, and complex background. Our approach is
based on building multi skin color clustering models using HSV color space, multi-level segmentation, and rule-based
classifier. We proposed to use four skin color clustering models instead of single skin clustering model, namely:
standard-skin model, shadow-skin model, light-skin model, high-red-skin model. We made an independent skin color
clustering models by converting 3-D color space to 2-D without losing color information in order to find the
classification boundaries for each skin color pattern class in 2-D. Once we find the classification boundaries, we process
the input image with the first-level skin-color segmentation to produce four layers; each layer reflecting its skin-color
clustering model. Then an iterative rule-based region grow is performed to create one solid region of interest which is
presumed to be a face candidate region that will be passed to the second-level segmentation. In this approach we
combine pixel-based segmentation and region-based segmentation using the four skin layers. We also propose skin-color
correction (skin lighting) at shadow-skin layer to improve detection rate.
In the second-level segmentation we use gray scale to segment the face candidate region into the most significant
features using thresholding. Next step is to compute the X-Y-reliefs to locate the accurate position of facial features in
each face candidate region and match it with our geometrical knowledge in order to classify the face candidate region to
a face or non-face region. We present experimental results of our implementation and demonstrate the feasibility of our
approach to be general purpose skin color segmentation for face detection problem.
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