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Alignment-Robust Cancelable Biometric Scheme for Iris Verification
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AI
DOI：10.1109/TIFS.2022.3208812.png)
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Abstract
En 中文
In this paper, we propose a histogram of oriented gradient inspired cancelable biometrics - Random Augmented Histogram of Gradients (R center dot HoG) for iris template protection. The proposed R center dot HoG is built upon on two main components: 1) column vector random augmentation and 2) gradient orientation grouping mechanisms to transform the unaligned irisCode feature into the alignment-robust cancelable template. The alignment-robust property of the proposed R center dot HoG enables the fast template comparison which is crucial for an efficient authentication process. Experiments were performed on CASIA-IrisV3-Internal and CASIA-IrisV4-Thousand datasets. The results demonstrate the proposed R center dot HoG could achieve acceptable verification performance in both datasets. Other than that, the irreversibility and security properties are studied based on major security and privacy attacks in biometric system. Lastly, results from the benchmarking evaluation framework show the proposed method is satisfying the unlinkability property.
Keywords:
Iris
cancelable biometrics
histogram of oriented gradient
security and privacy
Journal
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5.2K
Citations:
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