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Empirical mode decomposition-based face recognition system

Empirical mode decomposition-based face recognition system
 
Gallego Jutglà, Esteve ; Lopez-de-Ipiña, Karmele ; Solé-Casals, Jordi
2013

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Abstract

In this work we explore the multivariate empirical mode decomposition combined with a Neural Network classifier as technique for face recognition tasks. Images are simultaneously decomposed by means of EMD and then the distance between the modes of the image and the modes of the representative image of each class is calculated ...»»»»
In this work we explore the multivariate empirical mode decomposition combined with a Neural Network classifier as technique for face recognition tasks. Images are simultaneously decomposed by means of EMD and then the distance between the modes of the image and the modes of the representative image of each class is calculated using three different distance measures. Then, a neural network is trained using 10- fold cross validation in order to derive a classifier. Preliminary results (over 98 % of classification rate) are satisfactory and will justify a deep investigation on how to apply mEMD for face recognition.^^^^

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Conference object

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(c) Springer (The original publication is available at www.springerlink.com)
 
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Citation:

GALLEGO-JUTGLÀ, E., LOPEZ-DE-IPIÑA, K., MARTÍ-PUIG, P. and SOLÉ CASALS, J., 2013. Empirical mode decomposition-based face recognition system, International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2013, 11 February 2013 through 14 February 2013 2013, pp. 445-450.