Minutiae and modified Biocode fusion for fingerprint-based key generation

  • Authors:

  • Eryun Liu;Jimin Liang;Liaojun Pang;Min Xie;Jie Tian

  • Affiliations:

  • Life Sciences Research Center, School of Life Sciences and Technology, Xidian University, Xian, Shaanxi 710071, China and School of Electronic Engineering, Xidian University, Xian, Shaanxi 710071, ...;Life Sciences Research Center, School of Life Sciences and Technology, Xidian University, Xian, Shaanxi 710071, China;Ministry of Education Key Laboratory of Computer Network and Information Security, School of Telecommunication Engineering, Xidian University, Xian, Shaanxi 710071, China;Ministry of Education Key Laboratory of Computer Network and Information Security, School of Telecommunication Engineering, Xidian University, Xian, Shaanxi 710071, China;Life Sciences Research Center, School of Life Sciences and Technology, Xidian University, Xian, Shaanxi 710071, China and Institute of Automation, Chinese Academy of Sciences, Beijing 100190, Chin ...

  • Venue:
  • Journal of Network and Computer Applications
  • Year:
  • 2010

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Abstract

Key generation from biometrics has been studied intensively in recent years, linking a key with certain biometric enhances the strength of identity authentication. But the state-of-the-art key generation systems are far away from practicality due to low accuracy. The special manner of biometric matching makes a single feature based key generation system difficult to obtain a high recognition accuracy. Integrating more features into key generation system may be a potential solution to improve the system performance. In this paper, we propose a fingerprint based key generation system under the framework of fuzzy extractor by fusing two kinds of features: minutia-based features and image-based features. Three types of sketch, including minutiae based sketch, modified Biocode based sketch, and combined feature based sketch, are constructed to deal with the feature differences. Our system is tested on FVC2002 DB1 and DB2, and the experimental results show that the fusion scheme effectively improves the system performance compared with the systems based only on minutiae or modified Biocode.