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A High-Security-Level Iris Recognition System Based on Multi-Scale Dominating Feature Points
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AI
DOI：10.1109/LSP.2024.3411513.png)
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摘要
En 中文
In this letter, an error-correction-based iris recognition (EC-IR) scheme, which utilizes multi-scale dominating feature points (msDFPs), is constructed to enhance the security level against a stricter concern of error-correction-based attack, where the intruder is assumed to be fully aware of the architecture of the adopted error-correcting code. The extraction method of the msDFPs is proposed to alter the essence of raw iris data. Accordingly, it is shown that the proposed msDFPs-based EC-IR scheme provides a balanced design which guarantees both a large value of security bits and an enhanced recognition performance, and is particularly suited for real-world applications where a high-level security is paramount.
Keyword:
Iris recognition
Security
Feature extraction
Parity check codes
Benchmark testing
Databases
Biometrics (access control)
Biometric
cryptosystem
error-correcting codes
fuzzy commitment
iris
multi-scale dominating feature points. recognition accuracy
template protection
期刊
IF:
9.6
论文数:
1.1W
被引数:
1.7W
机构
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