In this paper we address the problem of face detection and recognition of grey scale frontal view images. We propose a face recognition system based on probabilistic neural networks (PNN) architecture. The system is implemented using voronoi/ delaunay tessellations and template matching. Images are segmented successfully into homogeneous regions by virtue of voronoi diagram properties. Face verification is achieved using matching scores computed by correlating edge gradients of reference

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... The advantage of classification using PNN models is its short training time. The correlation based template matching guarantees good classification results. Keywords-voronoi / delaunay triangulation; ellipse fitting; template matching; cross correlation; edge gradients; peak to side lobe ratio; probabilistic radial basis neural networks I.