Iris Liveness Detection Using Fragmental Energy of Haar Transformed Iris Images Using Ensemble of Machine Learning Classifiers

Contactless verification is possible with iris biometric identification,which helps prevent infections like COVID-19 from spreading.Biometric systems have grown unsteady and dangerous as a result of spoofing assaults employing contact lenses,replayed the video,and print attacks.The work demonstrates an iris liveness detection approach by utilizing fragmental coefficients of Haar transformed Iris images as signatures to prevent spoofing attacks for the very first time in the identification of iris liveness.Seven assorted feature creation ways are studied in the presented solutions,and these created features are explored for the training of eight distinct machine learning classifiers and ensembles.The predicted iris liveness identification variants are evaluated using recall,F-measure,precision,accuracy,APCER,BPCER,and ACER.Three standard datasets were used in the investigation.The main contribution of our study is achieving a good accuracy of 99.18%with a smaller feature vector.The fragmental coefficients of Haar transformed iris image of size 8∗8 utilizing random forest algorithm showed superior iris liveness detection with reduced featured vector size(64 features).Random forest gave 99.18%accuracy.Additionally,conduct an extensive experiment on cross datasets for detailed analysis.The results of our experiments showthat the iris biometric template is decreased in size tomake the proposed framework suitable for algorithmic verification in real-time environments and settings.

IrisCodeNet:虹膜特征编码网络

使用有效的特征提取算法对虹膜纹理进行准确的表达是虹膜识别技术的关键。基于虹膜识别任务的特殊性,提出了用于虹膜特征编码的网络模型IrisCodeNet。该网络架构使用了改进的BasicBlock,并结合了可以扩大决策边界的损失函数AM-Softmax(additive margin softmax)。为了获取最佳的虹膜识别效果,对AM-Softmax的参数设置、虹膜图像预处理输入形式、数据增强方式、网络输入尺寸做了细致的研究。实验结果表明:使用IrisCodeNet训练得到的特征提取器在CASIA-Iris-Thousand、CASIA-Iris-Distance、IITD虹膜数据库上进行测试,所评估的等错误率(equal error rate,EER)和正确接受率(true acceptance rate,TAR)均远远超过了广泛应用的传统算法。特别地,IrisCodeNet无需传统的虹膜归一化或精确的虹膜分割步骤依然取得了极好的识别效果。并且使用Grad-CAM(gradient-weighted class activation mapping)算法进行了可视化分析,结果表明该网络框架有效地关注了虹膜纹理信息,从而证明了IrisCodeNet具有较强的虹膜纹理特征提取能力。

Iris Segmentation Based on Matting

In this paper,we aim to propose a novel and effective iris segmentation method that is robust to uneven light intensity and different kinds of noises such as occlusion by light spots,eyelashes,eyelids,specta-cle-frame,etc.Unlike previous methods,the proposed method makes full use of gray intensities of the iris image.Inspired by the matting algorithm,a premier assumption is made that the foreground and background images of the iris image are both locally smooth.According to the RST algorithm,trimaps are built to provide priori in-formation.Under the assumption and priori,the optimal alpha matte can be obtained by least square loss function.A series of effective post processing methods are applied to the alpha image to obtain a more precise iris seg-mentation.The experiment on CASIA-iris-thousand database shows that the proposed method achieves a much better performance than conventional methods.Our experimental results achieve 20.5%and 26.4%,more than the well-known integro-differential operator and edge detection combined with Hough transform on iris seg-mentation rate respectively.The stability and validity of the proposed method is further demonstrated through the complementary experiments on the challenging iris images.

Implementation of the Hough Transform for Iris Detection and Segmentation

The iris is used as a reference for the study of unique biometric marks in people. The analysis of how to extract the iris characteristic information represents a fundamental challenge in image analysis, due to the implications it presents: detection of relevant information, data coding schemes, etc. For this reason, in the search for extraction of useful and characteristic information, approximations have been proposed for its analysis. In this article, it is presented a scheme to extract the relevant information based on the Hough transform. This transform helps to find primitive geometries in the irises, which are used to characterize each one of these. The results of the implementation of the algorithm of the Hough transform applied to the location and segmentation of the iris by means of its circumference are presented in the paper. Two public databases of iris images were used: UBIRIS V2 and CASIA-IrisV4, which were acquired under the same conditions and controlled environments. In the pre-processing stage the edges are found from the noise elimination in the image through the Canny detector. Subsequently, to the images of the detected edges, the Hough transform is applied to the disposition of the geometries detected.

Biometric Signature of Private Key by Reliable Iris Recognition Based on Flexible-ICA Algorithm

The numerical world is under a fast development generating facilities and threats. The recommended solutions are especially the protection of information in all its states. The levels of protection show a discrepancy from an application to another;governmental, commercial or even cybercriminal. The infrastructure used in modern cryptography is based on public key cryptosystem. The problem is how to make safe the private key and to memorize it without difficulties and damages. This paper introduces a biometric solution of owner signature generating an encryption of the key using the iris recognition kept in a smart card. Several precautions were taken to guarantee the safety and the availability of the use of the private key. They are two essential goals to attest: the quality of the service and the robustness of suggested safety. Being the quality of the service, the used iris recognition is based on a new emerging method founded on Flexible-ICA algorithm. This method offers a better Equal Error rate compared to other methods previously used. This quality of recognition was also reinforced by an encoding of error using a flag and finally Reed Solomon encoder. For recommended safety, a scheme based on block encryption is used. The proposed scheme is Propagating Cipher Block chaining which offers a very propagation of a high level of confusion and diffusion. Indeed, the robustness of this cryptographic process was studied by setting up strict criteria of safety.

Design of iris recognition system based on DSP and ZigBee

Due to complex computation and poor real-time performance of the traditional iris recognition system,iris feature is extracted by using amplitude and phase information of the mean image blocks based on Gabor filtering on image,and the k-nearest neighbor algorithm is combined to complete iris recognition function.The recognition reduces the recognition time and improves the recognition accuracy.At the same time,identification result is transmitted to the cloud server through ZigBee network to solve diffcult wiring problem.The experiment shows the system runs stably and has fast recognition speed.It has been applied to a security system.

Quantitative Real Time Measurement of Iris Configuration in Human Eyes

Purpose: To evaluate intraobserver and interobserver reproducibility of real time measurement of iris morphology in living human eyes.Methods: Base on the platform of software (Autocad, version 12), we developed an ultrasound biomicroscopy (UBM) image asisstant measuring system. By using the system, we can perform the iris configuration quantitative measurement in living eyes. The measuring parameters including: iris rest length,radius of iris curvature,and the thickness in different parts of iris. Ten anterior segment images of one normal individual were obtained by a single operator to evaluate the intraobserver reproducibility of image capture, and ten times measurement of one image were performed by a single operator to assess the reproducibilityof image measurement. The measurement of three independent observers were compared to investigate interobserver reproducibility in quantitative measurement. Intraobserver and interobserver reproducibility of measurement were assessed by calculating the

CASIA-Iris-Africa:A Large-scale African Iris Image Database

Iris biometrics is a phenotypic biometric trait that has proven to be agnostic to human natural physiological changes.Research on iris biometrics has progressed tremendously,partly due to publicly available iris databases.Various databases have been available to researchers that address pressing iris biometric challenges such as constraint,mobile,multispectral,synthetics,long-distance,contact lenses,liveness detection,etc.However,these databases mostly contain subjects of Caucasian and Asian docents with very few Africans.Despite many investigative studies on racial bias in face biometrics,very few studies on iris biometrics have been published,mainly due to the lack of racially diverse large-scale databases containing sufficient iris samples of Africans in the public domain.Furthermore,most of these databases contain a relatively small number of subjects and labelled images.This paper proposes a large-scale African database named Chinese Academy of Sciences Institute of Automation(CASIA)-Iris-Africa that can be used as a complementary database for the iris recognition community to mediate the effect of racial biases on Africans.The database contains 28717 images of 1023 African subjects(2046 iris classes)with age,gender,and ethnicity attributes that can be useful in demographically sensitive studies of Africans.Sets of specific application protocols are incorporated with the database to ensure the database’s variability and scalability.Performance results of some open-source state-of-the-art(SOTA)algorithms on the database are presented,which will serve as baseline performances.The relatively poor performances of the baseline algorithms on the proposed database despite better performance on other databases prove that racial biases exist in these iris recognition algorithms.

采用双流网络结构的虹膜卷缩轮检测方法

针对虹膜卷缩轮检测易受干扰而导致边界定位波动的问题,提出一种基于双流网络结构的虹膜卷缩轮检测方法。在归一化图像中,利用双流网络结构分别提取结构特征和纹理特征。融合模块融合来自不同流的特征,得到初定位区域。对该区域进行滤波操作,去除噪声干扰。利用边缘梯度算子检测、提取卷缩轮。实验结果表明,该方法正确检出率为91.2%,边缘定位AP值为0.706,平均检测速度为2.3秒/幅,相比其它算法,存在复杂干扰的情况下,保证检出率和检测速度的基础上,降低了边界波动。

异质虹膜识别研究综述

虹膜图像采集环境和设备的不同导致虹膜注册和识别样本差异较大,给传统的虹膜识别技术带来了挑战。异质虹膜识别问题已成为学术界和工业界关注的焦点。文中从不同层级、样本差异性以及单源和多源3个角度对现有的异质虹膜识别方法进行了分类和综述,总结了目前异质虹膜识别的最新进展。按照跨质量、跨设备和跨光谱的分类对现有的异质虹膜数据集进行综述,并总结概述虹膜识别评价指标,以便研究人员更好地评估和验证算法的性能。最后,从环境鲁棒性、数据异质性建模和多模态融合3个方向,对未来异质虹膜识别研究的发展方向进行了展望。

基于投影约束和随机采样Hough变换的虹膜分割方法

非合作式虹膜图像的采集导致图像中具有大量干扰和噪声,因此,提出基于投影约束和随机采样Hough变换的虹膜分割方法提取虹膜有效区域。对虹膜二值图像进行投影粗定位虹膜的外轮廓圆心和半径,通过圆心和半径确定虹膜的大致区域,在该区域上,使用随机采样的Hough变换确定虹膜的内外轮廓,从而提高了虹膜分割的准确性。实验证明,与现有方法相比虹膜分割方法错误指标E1和E2最多提高8%和20%,具有更低的错误率和较高的时间效率。

Phase Correlation Based Iris Image Registration Model

Iris recognition is one of the most reliable personal identification methods. In iris recognition systems, image registration is an important component. Accurately registering iris images leads to higher recognition rate for an iris recognition system. This paper proposes a phase correlation based method for iris image registration with sub-pixel accuracy. Compared with existing methods, it is insensitive to image intensity and can compensate to a certain extent the non-linear iris deformation caused by pupil movement. Experimental results show that the proposed algorithm has an encouraging performance.

An image segmentation based method for iris feature extraction

In this article, the local anomalistic blocks such as crypts, furrows, and so on in the iris are initially used directly as iris features. A novel image segmentation method based on intersecting cortical model （ICM） neural network was introduced to segment these anomalistic blocks. First, the normalized iris image was put into ICM neural network after enhancement. Second, the iris features were segmented out perfectly and were output in binary image type by the ICM neural network. Finally, the fourth output pulse image produced by ICM neural network was chosen as the iris code for the convenience of real time processing. To estimate the performance of the presented method, an iris recognition platform was produced and the Hamming Distance between two iris codes was computed to measure the dissimilarity between them. The experimental results in CASIA v1.0 and Bath iris image databases show that the proposed iris feature extraction algorithm has promising potential in iris recognition.

虹膜识别技术进展与趋势

虹膜识别具有很高的精度和稳定性,已广泛应用在金融、边防和门禁等领域.经过20多年的发展,虹膜识别在成像装置和识别算法方面均取得了显著的进展.一方面,虹膜成像装置的成像距离越来越远、成像范围越来越大、重量体积越来越小,明显提高了虹膜识别系统的易用性.另一方面,大规模的应用促进了许多低质量虹膜图像处理、快速分类检索、跨设备识别和安全隐私保护方法的研究.未来几年,虹膜识别将在技术、应用和行业等方面呈现出以下六大发展趋势:从近红外到多光谱、从人工设计到数据驱动、从人配合机器到机器配合人、从固定设备到移动互联、从可控环境到复杂场景、从各行其是到标准规范.

Hough变换在虹膜区域分割中的应用

Hough变换是计算机视觉中用来检测物体几何形状的常用算法,它可以容易地检测出图像中出现的直线、圆以及其他形状。在虹膜识别系统中,确定虹膜区域正是需要从图像中提取出圆形的虹膜边界和眼皮部分。对Hough变换做一介绍,并对虹膜图像分割中的应用进行研究。仿真结果表明,Hough变换对于已知形状的图像分割是有效的,在虹膜区域分割精度是很高的。

虹膜识别技术的发展与应用

在对虹膜识别技术的研究现状、识别框架、系统构成等进行全面分析的基础上,介绍了虹膜图像获取、图像预处理、特征提取、特征匹配及性能评价指标等主要内容。剖析了该技术面临着高质量图像采集困难,稳定性、可行性有待验证等主要问题,提出了该技术的研究发展方向及应用前景,包括虹膜特征信息与其他生物特征信息及非生物特征信息相融合;建立虹膜特征识别的网络身份认证系统;高效快速的识别算法及通用性和兼容性强的虹膜识别芯片。

二维Gabor小波在虹膜识别中的应用

二维连续小波变换具有尺度伸缩、平面位移和旋转能力,被广泛应用于检测图像的局部特性,二维Gabor小波变换属于二维连续小波变换,它非常适合于提取图像细节纹理的特征。针对虹膜纹理的局部特性,将二维Gabor小波应用于虹膜识别中。实验结果表明,二维Gabor小波能有效地提取虹膜纹理特征,从而达到虹膜识别的目的。

用Gabor滤波实现虹膜图像纹理编码

针对虹膜纹理的幅度和相位信息特征,利用二维Gabor滤波器族可以很好地模拟皮层简单细胞的二维感受野轮廓,能够最大限度的提供图像局部方向和频率信息的特点,提出一种基于二维Gabor函数族对虹膜图像进行子块分解滤波的改进编码算法。实验结果表明,该方法能有效的提取虹膜纹理特征,从而达到虹膜识别的目的。

基于圆弧逼近的虹膜定位方法

在虹膜识别系统中,如何提高虹膜定位的速度和精度是急需解决的重要问题。针对虹膜边缘图像中的圆形局部畸变的情况,在虹膜定位中,采用圆弧逼近的方法,第1步进行圆弧参数的分段拟合,第2步进行圆弧参数动态聚类,完成虹膜的内边缘定位,在内边缘定位的基础上,实现虹膜外边缘定位。实验结果表明,在同等情况下,比基于J.D圆探测算法和Hough变换算法的虹膜定位速度快,精度高。

基于几何特征的虹膜定位算法

提出了利用虹膜边缘图象的几何特征以及圆相交弦的性质进行虹膜定位算法 .首先根据虹膜图象的整体灰度分布信息 ,利用边缘检测算子提取虹膜的内边缘图象 ,然后利用圆的相交弦性质以及投票策略提取虹膜的中心 ,最后利用 Hough变换的半径直方图投票策略提取虹膜内外径 .通过仿真实验的对比结果表明 ,该算法提高了虹膜定位的速度 。