The lack of robustness against image quality degradation is a open issue in fingerprint verification. It has been found in previous studies that the behavior of a fingerprint verification system may vary depending on the quality of the fingerprints. In this paper, we study the performance for individual users under varying image conditions using a multisensor database acquired with three different fingerprint sensors. We propose a user-dependent score normalization scheme that exploits quality information, reaching an EER improvement of  15% in one particular sensor. We have also included the proposed score normalization scheme in a multisensor fingerprint verification system that combines the three sensors, obtaining an EER improvement of  13% in the best case.