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Low-Complexity Iris Coding and Recognition Based on Directionlets
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DOI：10.1109/TIFS.2009.2024025.png)
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摘要
En 中文
A novel iris recognition method is presented. In the method, the iris features are extracted using the oriented separable wavelet transforms (directionlets) and they are compared in terms of a weighted Hamming distance. The feature extraction and comparison are shift-, size-, and rotation-invariant to the location of iris in the acquired image. The generated iris code is binary, whose length is fixed ( and therefore commensurable), independent of the iris image, and comparatively short. The novel method shows a good performance when applied to a large database of irises and provides reliable identification and verification. At the same time, it preserves conceptual and computational simplicity and allows for a quick analysis and comparison of iris samples.
Keyword:
Biometrics
directional transform
directional vanishing moments (DVMs)
feature extraction
iris recognition
personal identification
wavelet transform (WT)
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2.3W
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