Face recognition improvement using soft biometrics

In this work we are interested in soft facial biometrics, a new field that aims at strengthening the performance of primary biometric systems based on traditional ways of biological type (DNA, saliva), morphological (face, iris, fingerprint) or behavioral (signature, handwriting, voice). We propose three types of facial soft biometrics: facial measurements, skin color and hair color. The results show that the fusion of these modalities with the primary face recognition system based on wavelet characterization and SVM training has increased the recognition rate and has decreased the equal error rate.