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Iris Recognition using Robust Localization and Nonsubsampled Contourlet Based Features

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Abstract

The conventional iris recognition methods do not perform well for the datasets where the eye image may contain nonideal data such as specular reflection, off-angle view, eyelid, eyelashes and other artifacts. This paper gives contributions for a reliable iris recognition method using a new scale-, shift- and rotation-invariant feature-extraction method in time-frequency and spatial domains. Indeed, a 2-level nonsubsampled contourlet transform (NSCT) is applied on the normalized iris images and a gray level co-occurrence matrix (GLCM) with 3 different orientations is computed on both spatial image and NSCT frequency subbands. Moreover, the effect of the occluded parts is reduced by performing an iris localization algorithm followed by a four regions of interest (ROI) selection. The extracted feature set is transformed and normalized to reduce the effect of extreme values in the feature vector. Next, significant features for iris recognition are selected by a two-step method composed by a filtering stage and wrapper based selection. Finally, the selected feature set is classified using support vector machine (SVM). The proposed iris identification method was tested on the public iris datasets CASIA Ver.1 and CASIA Ver.4-lamp showing a state-of-the-art performance.

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Notes

  1. Our reported results were obtained using the LOOCV method in the testing process.

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Authors and Affiliations

  1. Institute for Systems and Robotics (ISR-UC), Electrical and Computer Engineering Department, University of Coimbra, Coimbra, Portugal

    Sirvan Khalighi & Urbano Nunes

  2. Department of Computer and Information Technology Engineering, Azad University of Qazvin, Qazvin, Iran

    Fatemeh Pak

  3. Department of Information Systems Engineering, Concordia University, Montreal, Canada

    Parisa Tirdad

Authors
  1. Sirvan Khalighi
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  2. Fatemeh Pak
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  3. Parisa Tirdad
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  4. Urbano Nunes
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Correspondence to Sirvan Khalighi.

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Khalighi, S., Pak, F., Tirdad, P. et al. Iris Recognition using Robust Localization and Nonsubsampled Contourlet Based Features. J Sign Process Syst 81, 111–128 (2015). https://doi.org/10.1007/s11265-014-0911-2

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  • DOI: https://doi.org/10.1007/s11265-014-0911-2

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