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Sensors 2010, 10(9), 7896-7912; doi:10.3390/s100907896

Effective Fingerprint Quality Estimation for Diverse Capture Sensors

3,*  and 1
Received: 8 June 2010 / Revised: 2 July 2010 / Accepted: 11 August 2010 / Published: 26 August 2010
(This article belongs to the Special Issue Bioinspired Sensor Systems)
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Recognizing the quality of fingerprints in advance can be beneficial for improving the performance of fingerprint recognition systems. The representative features to assess the quality of fingerprint images from different types of capture sensors are known to vary. In this paper, an effective quality estimation system that can be adapted for different types of capture sensors is designed by modifying and combining a set of features including orientation certainty, local orientation quality and consistency. The proposed system extracts basic features, and generates next level features which are applicable for various types of capture sensors. The system then uses the Support Vector Machine (SVM) classifier to determine whether or not an image should be accepted as input to the recognition system. The experimental results show that the proposed method can perform better than previous methods in terms of accuracy. In the meanwhile, the proposed method has an ability to eliminate residue images from the optical and capacitive sensors, and the coarse images from thermal sensors.
Keywords: fingerprints; sensor; quality estimation; SVM; recognition fingerprints; sensor; quality estimation; SVM; recognition
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Xie, S.J.; Yoon, S.; Shin, J.; Park, D.S. Effective Fingerprint Quality Estimation for Diverse Capture Sensors. Sensors 2010, 10, 7896-7912.

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