This paper presents a bimodal biometric verification system based on the fusion of palmprint and face features at the matching-score level. The system combines a new approach to palmprint principal lines recognition based on hypotheses generation and evaluation and the well-known eigenfaces approach for face recognition. The experiments with different matching-score normalization techniques have been performed in order to improve the performance of the fusion at the matching-score level. A “chimerical” database consisting of 1488 palmprint and face image pairs of 241 persons was used in the system design (440 image pairs of 110 persons) and testing (1048 image pairs of 131 persons). The experimental results show that system performance is significantly improved over unimodal subsystems.