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Please use this identifier to cite or link to this item: http://purl.org/purl/4142

Title: Face Recognition using Probabilistic Neural Networks
Authors: Santhosh Kumar, G
Vinitha, K V
Keywords: voronoi / delaunay triangulation
ellipse fitting
template matching
cross correlation
edge gradients
peak to side lobe ratio
probabilistic radial basis neural networks
Issue Date: 2009
Publisher: IEEE
Abstract: 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 images. The advantage of classification using PNN models is its short training time. The correlation based template matching guarantees good classification results
Description: Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on
URI: http://dyuthi.cusat.ac.in/purl/4142
Appears in Collections:Dr.Santhosh Kumar G

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