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Fingerprint Quality Assessment

  • Michael Yi-Sheng Yao
  • Sharath Pankanti
  • Norman Haas

Abstract

For a particular biometric to be effective, it should be universal: Every individual in the target population should possess the biometrics, and every acquisition from each individual should provide useful information for personal identity verification or recognition. In other words, everybody should have the biometrics and it should be easy to sample or acquire. In practice, adverse signal acquisition conditions and inconsistent presentations of the signal often result in unusable or nearly unusable biometrics signals (biometrics samples). This is confounded by the problem that the underlying individual biometrics signal can vary over time due, for example, to aging. Hence, poor quality of the actual machine sample of a biometrics constitutes the single most cause of poor accuracy performance of a biometrics system. Therefore, it is important to quantify the quality of the signal, either for seeking a better representation of the signal or for subjecting the poor signal to alternative methods of processin g (e.g., enhancement [9]). In this chapter,1 we explore a definition of the quality of fingerprint impressions and present detailed algorithms to measure image quality. The proposed quality measure has been developed with the use of human annotated images, and tested on a large number of fingerprints of different modes of fingerprint acquisition methods.

Keywords

Quality Assessment Biometric System Dominant Direction Directional Block Measure Image Quality 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York, Inc. 2004

Authors and Affiliations

  • Michael Yi-Sheng Yao
  • Sharath Pankanti
  • Norman Haas

There are no affiliations available

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