Biometric Authentication: A Machine Learning Approach

10.6. Concluding Remarks

This chapter has introduced and reviewed different fusion techniques for multicue biometric authentication systems. The pros and cons of fusing biometric data at different levels have been discussed. A novel multisample fusion technique, which is general and applicable to both face and speaker recognition systems, was then proposed to fuse the scores obtained from speaker or face models. This is evident by promising experimental results using the HTIMIT corpus, NIST2001 speaker recognition benchmark test, and XM2VTSDB audio-visual database. The technique is also amenable to the fusion of AV data. It was found that error rate reduction of up to 83% can be achieved when the multisample fusion technique is applied to fuse ...