Comparison and combination of iris matchers for reliable personal authentication

Ajay Kumar Pathak, Arun Passi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

260 Citations (Scopus)


The personal identification approaches using iris images are receiving increasing attention in the biometrics literature. Several methods have been presented in the literature and those based on the phase encoding of texture information are suggested to be the most promising. However, there has not been any attempt to combine these approaches to achieve further improvement in the performance. This paper presents a comparative study of the performance from the iris authentication using Log-Gabor, Haar wavelet, DCT and FFT based features. Our experimental results suggest that the performance from the Haar wavelet and Log-Gabor filter based phase encoding is the most promising among all the four approaches considered in this work. Therefore, the combination of these two matchers is most promising, both in terms of performance and the computational complexity. Our experimental results from the all 411 users (CASIA v3) and 224 users (IITD v1) database illustrate significant improvement in the performance which is not possible with either of these approaches individually.
Original languageEnglish
Pages (from-to)1016-1026
Number of pages11
JournalPattern Recognition
Issue number3
Publication statusPublished - 1 Mar 2010


  • Biometrics
  • Iris
  • Personal authentication

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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