TY - GEN

T1 - Wet fingerprint recognition

T2 - 2011 International Joint Conference on Biometrics, IJCB 2011

AU - Krishnasamy, Prasanna

AU - Belongie, Serge

AU - Kriegman, David

PY - 2011

Y1 - 2011

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84856091203&partnerID=8YFLogxK

U2 - 10.1109/IJCB.2011.6117594

DO - 10.1109/IJCB.2011.6117594

M3 - Conference article

AN - SCOPUS:84856091203

JO - 2011 International Joint Conference on Biometrics, IJCB 2011

JF - 2011 International Joint Conference on Biometrics, IJCB 2011

Y2 - 11 October 2011 through 13 October 2011

ER -