Bimodal biometric verification with different fusion levels

In this paper, we propose the fusion of two unimodal biometric verification systems, based on off-line signature and handwriting. The fusion of modalities is made at four different levels. In the first case, the fusion is situated at the feature extraction level by concatenating the vectors relative to each modality. In the second case, the fusion is situated at the decision level by the logic operators dasiaANDpsila and dasiaORpsila. Fusion at the matching score level is realised with two methods: arithmetic average and support vector machines. Fusing information from biometric images is based on a discrete wavelet transform. According to 12000 samples of handwritings and signatures, the best results are obtained for the feature extraction level and the matching score level.