Résumé:
Facial recognition systems have become one of the most widely used systems in the fields of
security and surveillance. Despite significant technological advancements, their performance
is still affected by changes in shooting conditions, such as lighting and modifications to facial
features caused by aging or different facial expressions. This thesis aims to improve the
performance of facial recognition systems using a new DRB classifier. The proposed
solutions have led to significant improvements compared to other classifiers (NN classifier,
SVM). Image matching descriptors Gabor, LPQ, MBC, and IWBC were used in experiments
applied to the ORL, 15 Yale, Face94, Face95, Face96, and Jaffe databases, which are among
the most used in academic studies to compare the results and determine the degree of
improvement achieved
