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SOCO
2008
Springer

A face recognition system based on Pseudo 2D HMM applied to neural network coefficients

8 years 4 months ago
A face recognition system based on Pseudo 2D HMM applied to neural network coefficients
Face recognition from an image or video sequences is emerging as an active research area with numerous commercial and law enforcement applications. In this paper different Pseudo 2-dimension Hidden Markov Models (HMMs) are introduced for a face recognition showing performances reasonably fast for binary images. The proposed P2-D HMMs are made up of five levels of states, one for each significant facial region in which the input frontal images are sequenced: forehead, eyes, nose, mouth and chin. Each of P2-D HMMs has been trained by coefficients of an artificial neural network used to compress a bitmap image in order to represent it with a number of coefficients that is smaller than the total number of pixels. All the P2-D HMMs, applied to the input set consisting of the Olivetti Research Laboratory face database combined to others photos, have achieved good rates of recognition and, in particular, the structure 3-6-6-6-3 has achieved a rate of recognition equal to 100%. Keywords Face r...
Vitoantonio Bevilacqua, Lucia Cariello, Gaetano Ca
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where SOCO
Authors Vitoantonio Bevilacqua, Lucia Cariello, Gaetano Carro, Domenico Daleno, Giuseppe Mastronardi
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