An assessment of the human performance of iris identification

R.M. Guest, H. He, S.V. Stevenage, G.J. Neil

    Research output: Published contribution to conferencePaperpeer-review

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    Biometric iris recognition systems are widely used for a range of identity recognition applications and have been shown to perform with high accuracy. For large-scale deployments, however, system enhancements leading to a reduction in error rates are continually sought. In this paper we investigate the performance of human verification of iris images and compare against a standard computer-based method. Our results suggest that performance using the computer-based system is no better than performance of the human participants. Additionally and importantly, however, performance can be improved through incorporation of the human as a ‘second decision maker’. This fusion system yields a false acceptance rate of just 9% when disagreements are resolved in line with strengths of each ‘decision-maker’. The results are presented as an illustration of the benefits that can be gained when combining human and automated systems in biometric processing.
    Original languageEnglish
    Number of pages4
    Publication statusPublished - 2013


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