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 [1], CalTech [2] and CMU PIE [3] databases, demonstrate the ability of the proposed algorithm in detecting faces also in difficult conditions.

A Rough Fuzzy Neural Based Approach to Face Detection

PETROSINO, Alfredo;SALVI, Giuseppe
2010

Abstract

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 [1], CalTech [2] and CMU PIE [3] databases, demonstrate the ability of the proposed algorithm in detecting faces also in difficult conditions.
1-60132-154-6
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11367/32529
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