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Fingerprint Recognition


Fingerprints were one of the first biometrics to be adopted and have currently become synonymous with reliable personal identification. The FBI currently maintains more than 200 million fingerprint records on file. Fingerprints have several advantages over other biometrics, such as the following (i) Universality: A large majority of the human population has legible fingerprints and can therefore be easily authenticated. This exceeds the extent of the population who possess passports, ID cards or any other form of tokens. (ii)High distinctiveness: Even identical twins who share the same DNA have been shown to have different fingerprints, since the ridge structure on the finger is not encoded in the genes of an individual. Thus, fingerprints represent a stronger authentication mechanism than DNA. (iii)High performance: Fingerprints remain one of the most accurate biometric modalities available to date with jointly optimal FAR (false accept rate) and FRR (false reject rate). Forensic systems are currently capable of achieving FAR of less than 10-4 (NIST).

We are developing a wide range of algorithms related to different stages of fingerprint recognition. We have developed a new non-stationary fingerprint enhancement algorithm based on Fourier domain analysis and a partial fingerprint matching algorithm that uses novel approaches from graph and optimization theory. We have developed a chain code contour based feature extraction algorithm that has yielded better feature extraction efficiency than NIST fingerprint software. We are also working on new score computation algorithm that treats fingerprint verification as a classification problem and uses advances from machine learning to yield better recognition rates. We are also working on novel techniques for protecting the privacy and security of fingerprint templates that is based on symmetric hash functions.

Publications:

  • Sharat Chikkerur, Alexander N. Cartwright, and Venu Govindaraju, "Fingerprint Image Enhancement Using STFT Analysis" ,accepted, ICAPR 2005,UK
  • Sharat Chikkerur, Sharath Pankanti, Nalini Ratha, Ruud Bolle and Venu Govindaraju, "Novel Approaches for Minutiae Verification in Fingerprint Images",IEEE WACV 2005, Colardo, USA.[pdf..]
  • Sharat Chikkerur, Chaohang Wu and Venu Govindaraju, "A Systematic approach for feature extraction in fingerprint images", ICBA July 2004, Hong Kong.[pdf..]
  • V. Govindaraju, Z. Shi, and J. Schneider " Fingerprint Feature Extraction Using Chaincoded Contours ", AVBPA 2003
  • T. Jea and V. Govindaraju, "A Minutia-Based Partial Fingerprint Recognition System", Pattern Recognition 2005 [pdf..]