Combination of Genetic Algorithm and Neural Network to Select Facial Features in Face Recognition Technique

Taraneh Kamyab (University of North Carolina at Charlotte)
Haitham Daealhaq (University of Karbala)
Ali Mojarrad Ghahfarokhi (University of Michigan)
Fatemehalsadat Beheshtinejad (Islamic Azad University)
Ehsan Salajegheh (Tarbiat Modares University)

International Journal of Robotics and Control Systems
Vol 3, No 1 (2023)

Face recognition methods are computational algorithms that follow aim to identify a person's image according to the bank of images they have of different people. So far, various methods have been proposed for face recognition, which can generally be divided into two categories based on face structure and based on facial features. Based on this, many algorithms have been introduced and used for face recognition. Genetic algorithm has been one of the successful algorithms for face recognition. In this article, we first briefly explained the genetic algorithm and then used the combination of neural network and genetic algorithm to select and classify facial features The presented method has been evaluated using individual features and combined features of the face region. Composite features perform better than face region features in experimental tests. Also, a comprehensive comparison with other facial recognition techniques available in the FERET database is included in this paper. The proposed method has produced a classification accuracy of 94%, which is a significant improvement and the best classification accuracy among the results established in other studies.