Biometric image hashing techniques have been widely studied and seen progressive advancements. However, only a handful of available solutions provide two-factor cancelability while simultaneously satisfying the tradeoff among all criteria of template protection mechanisms. In this paper, we propose a novel scheme for generating a secure and robust hash from a fingerprint image using Fourier-Mellin transform and fractal coding. First, due to its invariance property, Fourier-Mellin transform is incorporated into the domain fingerprint minutiae blocks to provide feature alignment, therein generating a fixed-length minutiae representation for comparison. Then, dimensionality reduction and texture compression are exploited using fractal coding to generate a robust and compact hash for improved security and recognition. The experimental results demonstrate a favorable recognition performance on benchmarked state-of-the-art schemes from FVC2002 and FVC2004 fingerprint databases. The analyses prove our method's robustness and resiliency to security and privacy attacks. Our method also satisfies the revocability and unlinkability criteria of cancelable biometrics.

中文翻译：

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基于分形编码的鲁棒且免对齐指纹图像哈希


生物特征图像哈希技术已被广泛研究并取得了进步。然而，只有少数可用的解决方案提供双因素可取消性，同时满足模板保护机制的所有标准之间的权衡。在本文中，我们提出了一种使用傅里叶梅林变换和分形编码从指纹图像生成安全且鲁棒的哈希的新颖方案。首先，由于其不变性，傅里叶-梅林变换被合并到域指纹细节块中以提供特征对齐，从而生成固定长度的细节表示用于比较。然后，使用分形编码进行降维和纹理压缩，生成稳健且紧凑的散列，以提高安全性和识别能力。实验结果表明，FVC2002 和 FVC2004 指纹数据库的基准最先进方案具有良好的识别性能。分析证明了我们的方法对安全和隐私攻击的稳健性和弹性。我们的方法还满足可取消生物识别技术的可撤销性和不可链接性标准。