Multimodal Fusion for Robust Identity Authentication: Role of Liveness Checks
Girija Chetty, Emdad Hossai · InTech eBooks · 2011
Most of the current biometric identity authentication systems currently deployed are based on modeling the identity of a person based on unimodal information, i.e. face, voice, or fingerprint features.Also, many current interactive civilian remote human computer interaction applications are based on speech based voice features, which achieve significantly lower performance for operating environments with low signal-to-noise ratios (SNR).For a long time, use of acoustic information alone has been a great success for several automatic speech processing applications such as automatic speech transcription or speaker authentication, while face identification systems based visual information alone from faces also proved to be of equally successful.However, in adverse operating environments, performance of either of these systems could be suboptimal.Use of both visual and audio information can lead to better robustness, as they can provide complementary secondary clues that can help in the analysis of the primary biometric signals (Potamianos et al (2004)).The joint analysis of acoustic and visual speech can improve the robustness of automatic speech recognition systems (Liu et al (2002), Gurbuz et al (2002).There have been several systems proposed on use of joint face-voice information for improving the performance of current identity authentication systems.However, most of these state-of-the-art authentication approaches are based on independently processing the voice and face information and then fusing the scores -the score fusion (Chibelushi et al (2002), Pan et al (2000), Chaudari et.al.(2003)).A major weakness of these systems is that they do not take into account fraudulent replay attack scenarios into consideration, leaving them vulnerable to spoofing by recording the voice of the target in advance and replaying it in front of the microphone, or simply placing a still picture of the target's face in front of the camera.This problem can be addressed with liveness verification, which ensures that biometric cues are acquired from a live person who is actually present at the time of capture for authenticating the identity.With the diffusion of Internet based authentication systems for day-to-day civilian scenarios at a astronomical pace (Chetty and Wagner ( 2008)), it is high time to think about the vulnerability of traditional biometric authentication approaches and consider inclusion of liveness checks for next generation biometric systems.Though there is some work in finger print based liveness checking techniques (Goecke and Millar (2003), Molhom et al (2002)), there is hardly any work in liveness checks based on userwww.intechopen.com