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Fusing the information in visible light and near-infrared images for iris recognition

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Abstract

Automated human identification is a significant issue in real and virtual societies. Iris is a suitable choice for meeting this goal. In this paper, we present an iris recognition system that uses images acquired in both near-infrared and visible lights. These two types of images reveal different textural information of the iris tissue. We demonstrated the necessity to process both VL and NIR images to recognize irides. The proposed system exploits two feature extraction algorithms: one is based on 1D log-Gabor wavelet which gives a detailed representation of the iris region and the other is based on 1D Haar wavelet which represents a coarse model of iris. The Haar wavelet algorithm is proposed in this paper. It makes smaller iris templates than the 1D log-Gabor approach and yet achieves an appropriate recognition rate. We performed the fusion at the match score level and examined the performance of the system in both verification and identification modes. UTIRIS database was used to evaluate the method. The results were compared with other approaches and proved to have better recognition accuracy, while no image enhancement technique is utilized prior to the feature extraction stage. Furthermore, we demonstrated that fusion can compensate the lack of input image information, which can be beneficial in reducing the computation complexity and handling non-cooperative iris images.

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Acknowledgments

The authors wish to thank Hamid Soltanian-Zadeh, Ziaddin D. Kuzekanani, Mahdi S. Hosseini and Razi Mousavi for providing the UTIRIS database, which was generated in University of Tehran, Iran.

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Authors and Affiliations

  1. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran

    Faranak Shamsafar & Hadi Seyedarabi

  2. Faculty of Electrical and Computer Engineering, Babol (Nooshirvani) University of Technology, Babol, Iran

    Ali Aghagolzadeh

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  1. Faranak Shamsafar
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  2. Hadi Seyedarabi
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  3. Ali Aghagolzadeh
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Correspondence to Faranak Shamsafar.

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Shamsafar, F., Seyedarabi, H. & Aghagolzadeh, A. Fusing the information in visible light and near-infrared images for iris recognition. Machine Vision and Applications 25, 881–899 (2014). https://doi.org/10.1007/s00138-013-0572-3

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  • DOI: https://doi.org/10.1007/s00138-013-0572-3

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