A Speaker independent “Liveness” Te

In biometrics, it is crucial to detect impostors and thwart replay attacks. However, few researches have focused yet on the “liveness” verifi cation. This test ensures that biometric cues being acquired are actual measurements from a live person who is present at the time of capture. Here, we propose a speaker independent “liveness” verifi cation method for audiovideo identifi cation systems. It uses the correlation that exists between the lip movements and the speech produced. Two data analysis methods are considered to model this statistical link. Finally, according to tests carried out on the XM2VTS database, the best liveness verifi cation EER achieved is 14.5% .