Human face detection plays an important role in application such as video surveillance, human computer interface, face recognition, and face image database management. In this paper we propose, a novel scheme for human faces detection in color images under unconstrained scene conditions, such as the presence of a complex background and uncontrolled illumination. The proposed method adopts a specialized unsupervised neural network, to extract skin colour regions in the Lab colour space, obtained from the integration of the rough fuzzy set based scale space transform and neural clustering. A correlation-based method is then applied for the detection of ellipse regions. Experiments on three benchmark face databases, namely the IMM , CalTech  and CMU PIE  databases, demonstrate the ability of the proposed algorithm in detecting faces also in difficult conditions.
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