Fusing color and shape descriptors in the recognition of degraded iris images acquired at visible wavelengths

Authors:
Hugo Proença;Gil Santos
Affiliations:
Department of Computer Science, IT - Instituto de Telecomunicaçíes, SOCIA - Soft Computing and Image Analysis Group, University of Beira Interior, 6200-Covilhã, Portugal;Department of Computer Science, IT - Instituto de Telecomunicaçíes, SOCIA - Soft Computing and Image Analysis Group, University of Beira Interior, 6200-Covilhã, Portugal
Venue:
Computer Vision and Image Understanding
Year:
2012

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Abstract

Despite the substantial research into the development of covert iris recognition technologies, no machine to date has been able to reliably perform recognition of human beings in real-world data. This limitation is especially evident in the application of such technology to large-scale identification scenarios, which demand extremely low error rates to avoid frequent false alarms. Most previously published works have used intensity data and performed multi-scale analysis to achieve recognition, obtaining encouraging performance values that are nevertheless far from desirable. This paper presents two key innovations. (1) A recognition scheme is proposed based on techniques that are substantially different from those traditionally used, starting with the dynamic partition of the noise-free iris into disjoint regions from which MPEG-7 color and shape descriptors are extracted. (2) The minimal levels of linear correlation between the outputs produced by the proposed strategy and other state-of-the-art techniques suggest that the fusion of both recognition techniques significantly improve performance, which is regarded as a positive step towards the development of extremely ambitious types of biometric recognition.