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
