Pores and Ridges: Fingerprint Matching Using Level 3 Features

  • Authors:
  • Anil Jain;Yi Chen;Meltem Demirkus

  • Affiliations:
  • Michigan State University;Michigan State University;Michigan State University

  • Venue:
  • ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

Fingerprint friction ridge details are generally described in a hierarchical order at three levels, namely, Level 1 (pattern), Level 2 (minutiae points) and Level 3 (pores and ridge shape). Although high resolution sensors (隆芦1000dpi) have become commercially available and have made it possible to reliably extract Level 3 features, most Automated Fingerprint Identification Systems (AFIS) employ only Level 1 and Level 2 features. As a result, increasing the scan resolution does not provide any matching performance improvement [1]. We develop a matcher that utilizes Level 3 features, including pores and ridge contours, for 1000dpi fingerprint matching. Level 3 features are automatically extracted using wavelet transform and Gabor filters and are locally matched using the ICP algorithm. Our experiments on a median-sized database show that Level 3 features carry significant discriminatory information. EER values are reduced (relatively 隆芦20%) when Level 3 features are employed in combination with Level 1 and 2 features.