This paper presents a chaos-based cancelable biometric scheme for iris recognition. Instead of using original iris features, a masked version of the features is generated through chaotic map encryption for increasing the iris recognition system privacy. The proposed framework for iris recognition includes iris localization, normalization, and feature extraction with Gabor filter. Finally, chaotic encryption is used for generating cancelable IrisCodes. A modification of the Logistic map is included to increase the key space, and hence, the privacy is enhanced. The encryption key depends on the input image. So, the resultant encrypted feature vector is sensitive to the key. Thus, the encrypted feature vector is robust as the key space is large. The proposed iris recognition framework excludes the effects of eyelids and eyelashes and masks the original Gabor features to increase the level of security. Matching is performed with a Hamming Distance (HD) metric. The proposed framework achieves promising recognition rates of 99.08% and an Equal Error Rate (EER) of 1.17%.

中文翻译：

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基于改进Logistic映射的有效可消除虹膜识别方案

本文提出了一种基于混沌的可取消生物特征识别虹膜的方案。代替使用原始的虹膜特征，该特征的掩蔽版本通过混沌地图加密生成，以增加虹膜识别系统的隐私。提出的虹膜识别框架包括虹膜定位，归一化以及使用Gabor滤波器进行特征提取。最后，混沌加密用于生成可取消的IrisCode。包括对Logistic映射的修改以增加密钥空间，因此，提高了隐私性。加密密钥取决于输入图像。因此，所得的加密特征向量对密钥敏感。因此，当密钥空间很大时，加密的特征向量是健壮的。所提出的虹膜识别框架排除了眼睑和睫毛的影响，并掩盖了原始的Gabor功能以提高安全性。匹配使用汉明距离（HD）度量执行。拟议的框架实现了令人满意的识别率99.08％和相等错误率（EER）1.17％。