Fingerprint-quality index using gradient components

Sanghoon Lee, Heeseung Choi, Kyoungtaek Choi, Jaihie Kim

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)


Fingerprint image-quality checking is one of the most important issues in fingerprint recognition because recognition is largely affected by the quality of fingerprint images. In the past, many related fingerprint-quality checking methods have typically considered the condition of input images. However, when using the preprocessing algorithm, ridge orientation may sometimes be extracted incorrectly. Unwanted false minutiae can be generated or some true minutiae may be ignored, which can also affect recognition performance directly. Therefore, in this paper, we propose a novel quality-checking algorithm which considers the condition of the input fingerprints and orientation estimation errors. In the experiments, the 2-D gradients of the fingerprint images were first separated into two sets of 1-D gradients. Then, the shapes of the probability density functions of these gradients were measured in order to determine fingerprint quality. We used the FVC2002 database and synthetic fingerprint images to evaluate the proposed method in three ways: 1) estimation ability of quality; 2) separability between good and bad regions; and 3) verification performance. Experimental results showed that the proposed method yielded a reasonable quality index in terms of the degree of quality degradation. Also, the proposed method proved superior to existing methods in terms of separability and verification performance.

Original languageEnglish
Article number4668364
Pages (from-to)792-800
Number of pages9
JournalIEEE Transactions on Information Forensics and Security
Issue number4
Publication statusPublished - 2008 Dec

Bibliographical note

Funding Information:
Manuscript received January 06, 2008; revised August 19, 2008. Current version published November 19, 2008. This work was supported by the Korea Science and Engineering Foundation (KOSEF) through the Biometrics Engineering Research Center at Yonsei University. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Anil Jain.

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications


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