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 conferencePaper

Abstract

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
Pages623-626
Number of pages4
Publication statusPublished - 2013

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Biometrics
Fusion reactions
Processing

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Guest, R. M., He, H., Stevenage, S. V., & Neil, G. J. (2013). An assessment of the human performance of iris identification. 623-626.
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Guest, RM, He, H, Stevenage, SV & Neil, GJ 2013, 'An assessment of the human performance of iris identification' pp. 623-626.

An assessment of the human performance of iris identification. / Guest, R.M.; He, H.; Stevenage, S.V.; Neil, G.J.

2013. 623-626.

Research output: Published contribution to conferencePaper

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AU - Guest, R.M.

AU - He, H.

AU - Stevenage, S.V.

AU - Neil, G.J.

PY - 2013

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N2 - 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.

AB - 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.

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