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Iris Recognition based on Local Mean Decomposition |
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PP: 217-222 |
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Author(s) |
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Wei-Yu Han,
Wei-Kuei Chen,
Yen-Po Lee,
Kuang-shyr Wu,
Jen-Chun Lee,
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Abstract |
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| The increasing need for information security has led to more attention being given to biometrics-based, automated personal
identification. Among existing biometric approaches, the human iris is the most promising technique. In general, an iris recognition
algorithm includes four basic steps: image quality assessment, image preprocessing, image feature extraction, and image matching.
This paper proposes an iris image matching and recognition method based on local mean decomposition (LMD). The LMD is a multiresolution
decomposition technique employed as a low-pass filter and utilizes discriminating features for iris recognition. To evaluate
the performance of this novel approach, several similarity measures were used to assess the results based on experiments using both
the CASIA and ICE iris image databases. The results showed promising performance using any of the three measures. Therefore, the
LMD method is a useful tool for iris feature extraction and recognition. |
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