基于安全概略的可撤销掌纹模板生成算法

为了有效改进掌纹模板生成算法的识别率和安全性等性能,提出一种基于安全概略的可撤销掌纹模板生成算法。首先提取掌纹图像不同方向、不同尺度的Gabor幅值特征,并通过主成分分析（PCA）算法对其进行降维;然后将加密后的特征向量与BCH码异或融合,得到基于安全概略的可撤销掌纹模板。对比实验表明,该算法具有良好的识别性能,能较好地满足可撤销性、多样性和不可逆性,即便在单密钥丢失的情况下,也具有较高的识别率。     

基于Gabor滤波器与LDP掌纹可撤销模板生成方法

针对掌纹身份认证中存在着识别率和安全性较差的问题,提出一种基于多方向的Gabor滤波和局部方向模式（Local Directional Pattern,LDP）的自适应阈值特征编码方法mLGDP,在此基础上,进一步提出一种基于多方向Gabor滤波和LDP方法的自适应阈值差值特征编码方法mDLGDP,并将这两种方法的特征相融合,有效增强了原有掌纹模板间的多样性和识别率。通过对图像的特征编码进行分块处理,提取特征向量并二值化,再采用Bloom滤波器实现多对一映射和对掌纹图像的位置置乱,将得到置乱结果矩阵和用户密钥通过卷积运算进行不可逆变换,最终获得掌纹图像的可撤销模板。理论分析和实验表明,即使在密钥丢失时,分别使用两种改进方法依然可以保持较高的识别率,当使用两种特征相融合的方法时,识别率能够得到有效提高,且具有更好的安全性。     

PalmPhasor算法性能的理论分析

模板的安全性和隐私性是掌纹系统实际应用的关键问题,然而生物特征保护的多项指标通常相互冲突并且难以同时满足.作为解决上述冲突的一种可撤销掌纹编码算法,PalmPhasor实现了高效、安全的掌纹认证.建立了系统分析PalmPhasor性能的完整框架.为了便于具体分析,将情景分为4种情况,并且提供了支持相应分析的预备知识,包括辅助定理以及Gabor滤波掌纹图像实部和虚部分布特性.在统计学基础上建立的理论分析和实验结果均表明:即使在用户口令被盗的情况下,多方向分数级融合增强的PalmPhasor算法也可以同时有效地满足可撤销生物特征的4项指标.     

采样式多通道Gabor滤波对掌纹的特征提取和分类

掌纹识别已被证实为最方便和有效的身份识别方法之一。根据掌纹的性质提出了一种掌纹方向特征提取的新方法,该方法首先利用选取掌纹中最拟合椭圆的方法寻找感兴趣区域,然后利用适应人感官系统的多通道采样式Gabor滤波器进行滤波,并提出用根据掌纹纹理和方向特性动态选取Gabor滤波器参数的方法来设计滤波器。在滤波过程中,从不同分辨率入手,利用不同方向和宽度的滤波器分别对掌纹的主线、褶皱、嵴线进行提取,在极坐标系下用改进的环行方向投影算法计算块能量,并且进行编码。经过模糊C均值聚类方法验证,结果表明,该方法对于掌纹具有很强的识别能力。     

改进的BioHashing指纹模板保护算法

BioHashing是可撤销生物认证中广泛应用的身份认证方案,针对用户令牌泄露导致BioHashing识别性能严重退化的问题,提出一种改进的BioHashing指纹模板保护算法。该算法在量化过程中采用滑动窗口产生固定长度的二值序列,并结合滑动窗口带来的更大的密钥空间,有效提高了指纹特征自身的区分能力和安全性。理论分析和实验结果表明,改进方法产生的二值序列能有效保护指纹模板的原始特征信息,提高系统的识别性能。     

基于D-S证据理论的掌纹识别

研究了掌纹识别问题,对掌纹图像特征提取、多特征的融合技术作了一定程度的探讨。采用数学形态学方法提取掌纹线特征;基于Gabor滤波器描述掌纹图像的纹理特征。利用掌纹的线特征和纹理特征两个信息分别作两个分类器的特征,利用模糊规则求出各分类器的基本概率分配函数,最后利用D-S证据理论的合成法则对两个分类器的结果进行融合判决。实验结果表明,这种方法是有效的,可行的。     

基于细节点投影的可撤销指纹模板生成算法

为了改善指纹模板保护算法的可撤销性、不可逆性等性能,设计了一种基于细节点投影的可撤销指纹模板生成算法.首先对指纹图像进行预处理,提取指纹的细节点特征,并筛选出采样半径范围内的有效细节点,然后对细节点进行直线投影,将投影后的向量映射到二维网格,生成固定长度的一维比特串,再结合用户PIN码生成可撤销指纹模板.在指纹数据库FVC2002-DB1和DB2上的实验结果表明,该算法不仅提高了指纹模板认证的稳定性,而且在可撤销性、不可逆性和安全性等方面均具有较好性能.     

融合水平梯度与局部信息强度的掌纹识别算法

掌纹纹线特征是掌纹最有效的特征.由于在采集掌纹时不可避免地会产生尺度不一致、细微的旋转或平移等问题,使得准确地提取以及描述纹线特征成为掌纹识别的一大难点.针对这一问题,提出了一种融合水平梯度与局部信息强度的掌纹识别算法(Horizontal Gradient-Local Information Intensity,HG-LII).首先,使用不同的均值滤波模板消除细小、不规则、不稳定的掌纹纹线特征,对处理后的图像使用水平梯度算子得到水平方向的梯度图像,并进行二值化;其次使用分块思想计算掌纹纹线的信息强度,并将其作为特征向量;最后采用卡方距离进行匹配,判断掌纹所属类别.在PolyU掌纹库上的实验结果表明,该算法识别率达到99.89％,与传统的提取纹线算法相比,识别率有明显的提高,表明了该算法的有效性.     

基于指纹的可撤销Fuzzy vault方案

Fuzzy vault是一种用生物特征保护密钥的加密框架,其主要缺点在于攻击者可以通过交叉比较同一用户的不同vault来获得生物模板的准确信息,从而可以破解vault。提出了一种使用基于指纹细节点的可撤销的变换模板作为生成vault的模板,保护不同密钥时采用不同变换模板,从而解决了这个问题。采用以巴特沃斯低通滤波器为核的函数组作为生成可撤销模板的变换函数。此外还使用了用户口令加密vault,从而进一步增强了被保护密钥的安全性。     

一种可撤销的指纹模板保护方案

在指纹识别系统中,当用户的指纹模板被攻击者获取时,用户的隐私和安全就可能遭到威胁,因此,保护指纹特征模板已成为一个关键环节。尽管许多指纹模板保护方法已经被提出,但是要设计一个同时满足多样性、可撤销性、不可逆性和高性能的方案仍具有一定的挑战性。文章提出一种可撤销的指纹模板保护方案,将原始指纹细节点信息经过不可逆变换生成可撤销的比特串模板,其主要思想是:任选一个细节点作为基准点,与周围其他所有细节点进行两两比较,得到相对距离和方向场角度差;然后,将其量化并映射到一个定义的二维极坐标网格中;按照一定顺序读取网格单元中的数据,得到一个一维比特串模板。当比特串模板泄露时,通过改变用户口令PIN生成新的比特串模板,达到可撤销的目的。由于变换过程是不可逆的,所以即使攻击者获得比特串模板也不能恢复出原始指纹特征信息,保护了用户的隐私。在实验中,用指纹数据库FVC2004 DB1和FVC2004 DB2对文中方法与S.Wang提出的方法分别进行测试,实验结果显示,文章提出方法的性能优于S.Wang提出的方法,并且具有更高的安全性。     

Generating cancelable palmprint templates via coupled nonlinear dynamic filters and multiple orientation palmcodes

A novel scheme for generating cancelable palmprint templates is proposed in this paper. Firstly, a chaotic high speed stream cipher is implemented based on coupled nonlinear dynamic filters (CNDF), in which the CNDF are constructed to have flows inverse to each other. Secondly, renewable and privacy preserving palmprint templates are generated using the CNDF chaotic stream cipher with multiple orientation palmprint features obtained from a bank of Gabor filters and encoded in a phase-coding scheme. Compared with the standard palmprint templates, the cancelable templates have greater ability to discriminate palmprints from different hands by increasing the inter-class divergence of different palms more effectively, while maintaining the intra-class distance among palmprints of the same hands. Lastly, the matching stage is performed directly on the cancelable/encryption domain in parallel to accelerate matching and to protect user’s privacy. Several fusion rules are investigated for the matching scores of different directional PalmCodes to obtain the final matching score. Compared with Max, Min, Median and Product fusion rules, the Sum rule can greatly accelerate the speed and improve the performance Experimental results on the Hong Kong PolyU Palmprint Database verify that the proposed cancelable templates can achieve very high performance and security levels with a very strong ability to reissue palmprint templates. The proposed method can also be implemented at high speed, which satisfies the needs of real-time applications.     

Orientation selection using modified FCM for competitive code-based palmprint recognition

Coding-based methods are among the most promising palmprint recognition methods because of their small feature size, fast matching speed and high verification accuracy. The competitive coding scheme, one representative coding-based method, first convolves the palmprint image with a bank of Gabor filters with different orientations and then encodes the dominant orientation into its bitwise representation. Despite the effectiveness of competitive coding, few investigations have been given to study the influence of the number of Gabor filters and the orientation of each Gabor filter. In this paper, based on the statistical orientation distribution and the orientation separation characteristics, we propose a modified fuzzy C-means cluster algorithm to determine the orientation of each Gabor filter. Since the statistical orientation distribution is based on a set of real palmprint images, the proposed method is more suitable for palmprint recognition. Experimental results indicate that the proposed method achieves higher verification accuracy while compared with that of the original competitive coding scheme and several state-of-the-art methods, such as ordinal measure and RLOC. Considering both the computational complexity and the verification accuracy, competitive code with six orientations would be the optimal choice for palmprint recognition.     

基于Gabor局部相对特征的掌纹识别

Gabor变换是掌纹识别中提取纹理特征的一个重要工具,但其性能易受图像的变化以及不均衡噪声等因素影响,因此提出了一种基于Gabor局部相对特征的掌纹识别算法。该算法对原始图像进行微尺度不变Gabor滤波;结合分形学的思想,将滤波后的图像分成大小相等的子域,每个子域又分成多个相同的子块,计算每个子块与它所在子域的相对方差,将所有子块的相对方差排列组成表征图像的特征向量进行识别。该算法将微尺度不变与局部相对特性统一,所提取的特征对各种变化有很强的鲁棒性,提高了识别精度和效率。实验使用北京交通大学BJTU_PalmprintDB证明该算法的有效性。     

Generalized Gabor filters for palmprint recognition

Orientation-based coding approaches have recently been widely employed for face and palmprint recognition where generally, one starts with a set of Gabor filters to extract orientation information and then proceeds to code dominant orientations as features for each point of the palmprint. However, as the Gabor filter is developed to model two-dimensional receptive fields of simple cells in straits cortex, it might not be our best choice when dealing with curved and complex structures inherent in the palmprint texture. Motivated by this intuition, this paper shows that Gabor filters are a subset of a bigger family of filters which we refer to as generalized Gabor filter (GGF). Depending on the values of its parameters, a GGF takes a rather diverse shapes and orientations, which results in a potentially finer feature extraction capability. We show this improved capability by employing GGFs in the palmprint verification process. In applying our method, two different sub-banks of GGFs are defined for the orientation-based feature extraction of palmprints, and when compared with Gabor filters, it will be shown that GGFs have the upper hand in capturing orientation features. Furthermore, compared with the competitive code—one of the well-known orientation-based coding methods—the number of employed orientations is reduced to half. This would automatically compensate for a double usage of the filter banks, which otherwise could increase the time complexity of using GGFs. These ideas are further elaborated using a set of experiments on PolyU II and PolyU 2D/3D palmprint databases. The results show the preeminence of using GGFs both in terms of accuracy and efficiency.     

A combination of Genetic Algorithm,Particle Swarm Optimization and Neural Network for palmprint recognition

In this study, a new approach to the palmprint recognition phase is presented. 2D Gabor filters are used for feature extraction of palmprints. After Gabor filtering, standard deviations are computed in order to generate the palmprint feature vector. Genetic Algorithm-based feature selection is used to select the best feature subset from the palmprint feature set. An Artificial Neural Network (ANN) based on hybrid algorithm combining Particle Swarm Optimization (PSO) algorithm with back-propagation algorithms has been applied to the selected feature vectors for recognition of the persons. Network architecture and connection weights of ANN are evolved by a PSO method, and then, the appropriate network architecture and connection weights are fed into ANN. Recognition rate equal to 96% is obtained by using conjugate gradient descent algorithm.

     

Dual-key-binding cancelable palmprint cryptosystem for palmprint protection and information security

Biometric cryptosystems and cancelable biometrics are both practical and promising schemes to enhance the security and privacy of biometric systems. Though a number of bio-crypto algorithms have been proposed, they have limited practical applicability because they lack of cancelability. Since biometrics are immutable, the users whose biometrics are stolen cannot use bio-crypto systems anymore. Cancelable biometric schemes are of cancelability; however, they are difficult to compromise the conflicts between the security and performance. By embedded a novel cancelable palmprint template, namely “two dimensional (2D) Palmprint Phasor”, the proposed palmprint cryptosystem overcomes the lack of cancelability in existing biometric cryptosystems. Besides, the authentication performance is enhanced when users have different tokens/keys. Furthermore, we develop a novel dual-key-binding cancelable palmprint cryptosystem to enhance the security and privacy of palmprint biometric. 2D Palmprint Phasor template is scrambled by the scrambling transformation based on the chaotic sequence that is generated by both the user's token/key and strong key extracted from palmprint. Dual-key-binding scrambling not only has more robustness to resist against chosen plain text attack, but also enhances the secure requirement of non-invertibility. 2D Palmprint Phasor algorithm and dual-key-binding scrambling both increase the difficulty of adversary's statistical analysis. The experimental results and security analysis confirm the efficiency of the proposed scheme.