Many fingers wrinkle or shrivel when immersed in water. When used for biometric identification, the recognition rate for wrinkled fingers degrades. The impact of wrinkling has so far not been well-understood. In this study, we present an investigation of how the finger-skin expansion due to wrinkling impacts the quality of scanned fingerprints and characterize the qualitative changes that affect recognition. We also introduce the Wet and Wrinkled Finger (WWF) database that we will make available to other researchers. In this database of 300 fingers, 185 are visibly wrinkled after immersion; multiple images of dry and immersed fingerprints were acquired. In this paper, we present baseline recognition rates on WWF using two algorithms-a commercial fingerprint recognition algorithm and the publicly available Bozorth3 matcher. Specifically, we show a degradation in accuracy with both algorithms when comparing Dry-finger to Dry-finger verification with Dry-finger toWet-finger verification. We analyze performance on a per-finger basis and note a difference in accuracy amongst fingers, and as consequence make recommendations about which fingers to use in environments where fingers are apt to be wet. Additionally, we propose an implementation of a classifier that can decide if the incoming query is wrinkled.