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AVBPA
2005
Springer

Fingerprint Quality Indices for Predicting Authentication Performance

3 years 9 months ago
Fingerprint Quality Indices for Predicting Authentication Performance
The performance of an automatic fingerprint authentication system relies heavily on the quality of the captured fingerprint images. In this paper, two new quality indices for fingerprint images are developed. The first index measures the energy concentration in the frequency domain as a global feature. The second index measures the spatial coherence in local regions. We present a novel framework for evaluating and comparing quality indices in terms of their capability of predicting the system performance at three different stages, namely, image enhancement, feature extraction and matching. Experimental results on the IBM-HURSLEY and FVC2002 DB3 databases demonstrate that the global index is better than the local index in the enhancement stage (correlation of 0.70 vs. 0.50) and comparative in the feature extraction stage (correlation of 0.70 vs. 0.71). Both quality indices are effective in predicting the matching performance, and by applying a quality-based weighting scheme in the...
Yi Chen, Sarat C. Dass, Anil K. Jain
Added 26 Jun 2010
Updated 26 Jun 2010
Type Conference
Year 2005
Where AVBPA
Authors Yi Chen, Sarat C. Dass, Anil K. Jain
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