Binary Biometric Template Generation Towards Security and Class Separability

Eslam Hamouda, Xiaohui Yuan, Osama Ouda, Taher Hamza, Lei Chen

Research output: Contribution to book or proceedingChapter

3 Scopus citations

Abstract

Due to the wide usage of biometrics, its security issues deserve more attention. Many of biometric protection systems require the biometric templates to be presented in a binary form. Therefore, extracting binary templates from real-valued biometric data is a key step in biometric data protection systems. In addition to meeting the security and privacy requirements, binary biometric templates allow fast matching and reduced storage. The main challenge of these approaches is how to convert the real-valued templates into corresponding binary representation which retains the original information. In this paper, we present a novel method that employs Genetic Algorithms(GA)to generate a binarization scheme which used to transform the real-valued templates into robust binary ones. The main role of GA is to search for the optimal quantization and encoding parameters to generate the binarization scheme. Experiments were conducted with ORL face database for recognition. Our results demonstrated that binary templates achieved promising performance in terms of equal error rate for face recognition using a simple hamming distance classifier.
Original languageAmerican English
Title of host publicationProceedings of the International Conference on Computing, Communication, and Networking Technologies
DOIs
StatePublished - Jul 11 2014

Disciplines

  • Databases and Information Systems

Keywords

  • Binarization
  • Biometric template
  • Biometrics
  • Encoding
  • Genetic algorithm
  • Privacy
  • Quantization
  • Security

Fingerprint

Dive into the research topics of 'Binary Biometric Template Generation Towards Security and Class Separability'. Together they form a unique fingerprint.

Cite this