Fingerprint Image Enhancement: Algorithm and Performance Evaluation

Dept. of Comput. Sci., Michigan State Univ., East Lansing, MI
IEEE Transactions on Pattern Analysis and Machine Intelligence (Impact Factor: 5.78). 09/1998; 20(8):777 - 789. DOI: 10.1109/34.709565
Source: CiteSeer


In order to ensure that the performance of an automatic
fingerprint identification/verification system will be robust with
respect to the quality of input fingerprint images, it is essential to
incorporate a fingerprint enhancement algorithm in the minutiae
extraction module. We present a fast fingerprint enhancement algorithm,
which can adaptively improve the clarity of ridge and valley structures
of input fingerprint images based on the estimated local ridge
orientation and frequency. We have evaluated the performance of the
image enhancement algorithm using the goodness index of the extracted
minutiae and the accuracy of an online fingerprint verification system.
Experimental results show that incorporating the enhancement algorithm
improves both the goodness index and the verification accuracy

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Available from: Lin Hong, Nov 24, 2014
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    • "As opposed to human fingerprints, the frequency of the annual ring pattern is strongly varying. Similar as in our previous works (Schraml et al., 2014, 2015a) enhancement is based on the fingerprint enhancement approach presented by Hong et al. (1998). In Schraml et al. (2015a) we showed that a slight variation of the procedure utilized in Schraml et al. (2014) further improves the biometric system performance and is thus also used in this work. "
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    • "Hong et. al. [2] have an evergreen paper dealing with fingerprint enhancements, orientation using ridge alignments and also recovery of poor images. On a similar note, Jea and Govindaraju [3] have devised an algorithm for matching partial or low quality prints utilizing a neural network. "
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    • "These gaps establish reference points for the computation of the Region Of Interest (ROI) by detecting the boundary of the hand shape and the center from a transofrmed binary image [21]. Then a normalization is applied in order to have a specific mean and variance for all images [7]. "
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