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1.
基于局部小波变换与奇异值分解的虹膜识别算法   总被引:5,自引:0,他引:5  
虹膜识别以其唯一性、稳定性和非侵犯性等优点成为生物特征识别中极具发展潜力的身份识别技术。文章提出了一种基于局部小波变换和奇异值分解的虹膜识别算法。该算法首先对虹膜图像实行分窗小波分解,并对各窗口的子带图像作筛选处理,然后通过奇异值分解对筛选后的各子带图像作进一步的特征提取和压缩,得到虹膜识别特征。最后利用加权欧氏距离分类器进行识别。基于CASIA虹膜数据库的实验结果表明了该算法的有效性,为虹膜识别提供了一种新途径。  相似文献   

2.
Gait recognition using multi-bipolarized contour vector   总被引:2,自引:0,他引:2  
Gait recognition has recently attracted increasing interest from the biometric community. In this paper, we propose a simple yet powerful new feature called multi-bipolarized contour vector (MBCV) for gait recognition. The proposed MBCV feature consists of four components: (1) the Vertical Positive Contour Vector, (2) the Vertical Negative Contour Vector, (3) the Horizontal Positive Contour Vector, and (4) the Horizontal Negative Contour Vector. We furthermore develop a gait recognition system based on the proposed MBCV feature. The system consists of three steps: image preprocessing including background subtraction and silhouette normalization, extraction of the MBCV feature, and classification. To reduce the dimensionality of MBCV, we use principal component analysis (PCA). To solve the classification problem, we use the Euclidean distance and a nearest neighbor (NN) approach. Finally, we fuse the proposed gait features at all levels to improve recognition performance. The proposed recognition system is applied to the well-known NLPR gait database and its effectiveness is demonstrated via comparison with previous works.  相似文献   

3.
基于核主成分分析的步态识别方法   总被引:2,自引:0,他引:2  
陈祥涛  张前进 《计算机应用》2011,31(5):1237-1241
为了从多帧步态序列中更有效地提取步态特征并实时性地进行身份识别,提出一种有效的基于平均步态能量图(MGEI)的核主成分分析(KPCA)的身份识别方法。通过预处理技术提取出运动人体的侧面轮廓,根据步态下肢的摆动距离统计出步态周期,得到MGEI。KPCA采用非线性方法提取主成分,描述待识别图像中多个像素之间的相关性。利用KPCA的方法在高维空间对MGEI提取特征,选择合适的核函数,用方差倒数加权欧氏距离进行身份识别。实验结果表明,该算法具有较好的识别性能,并且耗时大大缩短。  相似文献   

4.
手部形状测量是人体测量的重要组成部分,也是身份认证的重要方法之一,基于二维图像的手部测量已经得到了广泛的研究与应用。提出一种新的手部图像测量点自动识别方法。该方法基于移动最小二乘图像配准技术;采用DOS方法提取两幅图像的匹配点;通过建立手部像素点集的8邻域无向带权图,在计算MLS配准权值时采用基于图Dijkstra最短路径距离来代替欧式距离。实验结果表明,与传统的基于特征提取和统计的方法相比,该方法具有统一、简洁、高效的特点,同时在测量点的识别率、鲁棒性以及精度方面也有明显提高。  相似文献   

5.
研究了心电(ECG)信号在身份识别中的应用,提出了基于过完备字典下稀疏编码的手指心电身份识别认证算法.在预处理阶段,对ECG信号进行预处理消噪,去除心电信号里的噪声、基线漂移和心率变异的干扰.在特征提取阶段,提取单周期心电信号构成特征向量并构建字典模型,用核奇异值分解(KSVD)训练成冗余字典,然后对每一部分特征向量进行稀疏编码,实现在该字典上的稀疏表示.在分类识别阶段,利用得到的稀疏系数矩阵构建特征模板向量作为特征参数.通过欧氏距离匹配输出个体身份信息,实现个体身份识别认证.通过两个手指心电信号数据库对该算法进行了性能测试,获得了较高的识别率.  相似文献   

6.
This paper introduces a novel approach for identity authentication system based on metacarpophalangeal joint patterns (MJPs). A discriminative common vector (DCV) based method is utilized for feature selection. In the literature, there is no study using whole MJP for identity authentication, exceptionally a work (Ferrer et al., 2005) using the hand knuckle pattern which is some part of the MJP draws the attention as a similar study. The originality of this approach is that: whole MJP is firstly used as a biometric identifier and DCV method is firstly applied for extracting the feature set of MJP. The developed system performs some basic tasks like image acquisition, image pre-processing, feature extraction, matching, and performance evaluation. The feasibility and effectiveness of this approach is rigorously evaluated using the k-fold cross validation technique on two different databases: a publicly available database and a specially established database. The experimental results indicate that the MJPs are very distinctive biometric identifiers and can be securely used in biometric identification and verification systems, DCV method is successfully employed for obtaining the feature set of MJPs and proposed MJP based authentication approach is very successful according to state of the art techniques with a recognition rate of between 95.33% and 100.00%.  相似文献   

7.
In this paper, we propose a novel view-invariant gait authentication method based on silhouette contours analysis and view estimation. The approach extracts Lucas-Kanade based gait flow image and head and shoulder mean shape (LKGFI-HSMS) of a human by using the Lucas-Kanade's method and procrustes shape analysis (PSA). LKGFI-HSMS can preserve the dynamic and static features of a gait sequence. The view between a person and a camera is identified for selecting the target's gait feature to overcome view variations. The similarity scores of LKGFI and HSMS are calculated. The product rule combines the two similarity scores to further improve the discrimination power of extracted features. Experimental results demonstrate that the proposed approach is robust to view variations and has a high authentication rate.   相似文献   

8.
Mining and visualization of time profiled temporal associations is an important research problem that is not addressed in a wider perspective and is understudied. Visual analysis of time profiled temporal associations helps to better understand hidden seasonal, emerging, and diminishing temporal trends. The pioneering work by Yoo and Shashi Sekhar termed as SPAMINE applied the Euclidean distance measure. Following their research, subsequent studies were only restricted to the use of Euclidean distance. However, with an increase in the number of time slots, the dimensionality of a prevalence time sequence of temporal association, also increases, and this high dimensionality makes the Euclidean distance not suitable for the higher dimensions. Some of our previous studies, proposed Gaussian based dissimilarity measures and prevalence estimation approaches to discover time profiled temporal associations. To the best of our knowledge, there is no research that has addressed a similarity measure which is based on the standard score and normal probability to find the similarity between temporal patterns in z-space and retains monotonicity. Our research is pioneering work in this direction. This research has three contributions. First, we introduce a novel similarity (or dissimilarity) measure, SRIHASS to find the similarity between temporal associations. The basic idea behind the design of dissimilarity measure is to transform support values of temporal associations onto z-space and then obtain probability sequences of temporal associations using a normal distribution chart. The dissimilarity measure uses these probability sequences to estimate the similarity between patterns in z-space. The second contribution is the prevalence bound estimation approach. Finally, we give the algorithm for time profiled associating mining called Z-SPAMINE that is primarily inspired from SPAMINE. Experiment results prove that our approach, Z-SPAMINE is computationally more efficient and scalable compared to existing approaches such as Naïve, Sequential and SPAMINE that applies the Euclidean distance.  相似文献   

9.
基于步态的特征识别是一种新兴的生物特征识别技术, 旨在通过人们走路的姿态进行身份和相关属性的分析. 与其他的生物识别技术相比, 基于步态的识别方法具有难隐藏性、非接触性和可远距离使用的优点. 本文设计出一个视频监控场景下基于单视角步态的人体身份及属性识别系统, 该系统通过图像处理方法从复杂的监控视频中实时检测出人体的步态, 经过利用深度学习训练过的算法进行分析后, 获取人体的身份、性别和年龄信息. 实验表明, 系统的身份识别准确率达98.1%, 性别预测准确率达97.1%, 年龄预测平均绝对误差为6.21岁, 实验结果均优于传统基准算法, 且系统开发成本低, 支持实时检测, 能充分满足中小规模步态研究与分析的需要.  相似文献   

10.
A gait recognition system using extended template features is presented. A proposed statistical approach is applied for feature extraction from spatial and temporal templates. This method can be used to reduce data dimensionality and to optimize the class separability of different gait sequences simultaneously. Dimensionality reduction is achieved by template extraction followed by principal component analysis. Gait recognition is achieved in the canonical space using a measure of accumulated distance as the metric. By incorporating spatial and temporal information into an extended feature, gait recognition becomes more robust and accurate than using spatial or temporal features alone.  相似文献   

11.
基于自适应特征选取的步态识别   总被引:1,自引:0,他引:1  
提出基于自适应特征选取的步态识别方法。采用新的特征提取方法,该方法将目标按人体结构特点划分为多个子区域,利用各个子区域的质心与头部质心的距离和夹角对步态特征进行描述。采用Boosting算法自适应选取最优特征序列,对识别结果进行加权处理。该方法结合了步态的动态和静态信息,实验结果表明该方法具有较高的识别性能。  相似文献   

12.
In this paper, a multi-view gait based human recognition system using the fusion of two kinds of features is proposed. We use cross wavelet transform to extract dynamic feature and bipartite graph model to extract static feature which are coefficients of quadrature mirror filter (QMF)-graph wavelet filter bank. Feature fusion is done after normalization. For normalization of features, min-max rule is used and mean-variance method is used to find weights for normalized features. Euclidean distance between each feature vector and center of the cluster which is obtained by k-means clustering is used as similarity measure in Bayesian framework. Experiments performed on widely used CASIA B gait database show that, the fusion of these two feature sets preserve discriminant information. We report 99.90% average recognition rate.   相似文献   

13.
Recognizing people by gait promises to be useful for identifying individuals from a distance; in this regard, improved techniques are under development. In this paper, an improved method for gait recognition is proposed. Binarized silhouette of a motion object is first represented by four 1-D signals that are the basic image features called the distance vectors. The distance vectors are differences between the bounding box and silhouette, and extracted using four projections to silhouette. Fourier Transform is employed as a preprocessing step to achieve translation invariant for the gait patterns accumulated from silhouette sequences that are extracted from the subjects’ walk in different speed and/or different time. Then, eigenspace transformation is applied to reduce the dimensionality of the input feature space. Support vector machine (SVM)-based pattern classification technique is then performed in the lower-dimensional eigenspace for recognition. The input feature space is alternatively constructed by using two different approaches. The four projections (1-D signals) are independently classified in the first approach. A fusion task is then applied to produce the final decision. In the second approach, the four projections are concatenated to have one vector and then pattern classification with one vector is performed in the lower-dimensional eigenspace for recognition. The experiments are carried out on the most well-known public gait databases: the CMU, the USF, SOTON, and NLPR human gait databases. To effectively understand the performance of the algorithm, the experiments are executed and presented as increasing amounts of the gait cycles of each person available during the training procedure. Finally, the performance of the proposed algorithm is comparatively illustrated to take into consideration the published gait recognition approaches.  相似文献   

14.
针对单项生物特征在网络身份认证过程中,可能由于用户身体受到伤病或污渍的影响而导致系统无法正常识别、合法用户无法登录的问题。提出了将多种生物特征用于网络身份认证的方法,并对相关技术进行了探讨。  相似文献   

15.
无线体域网是实现智慧健康的重要基础,但其采集的生理状态等敏感信息在开放的无线信道传输,攻击者容易伪装成合法用户获取用户隐私数据,因而身份认证成为挑战。对此,提出了一种将无线信道特征CSI与递归神经网络(RNN)相结合的身份认证方法,实现体域网中节点的有效身份认证。利用无线体域网中无线信道的物理层特征CSI作为合法节点认证的指纹特征。为了加快认证速度与效率,通过取特定环境下CSI的数据包,将数据包中子载波的特性作为RNN的输入量,训练出RNN模型来快速识别合法节点。通过实验将所提出的身份认证方法与利用RSS作为指纹特征的认证方法进行比较,结果表明所提方法的认证速度更快、准确率更高。  相似文献   

16.
用轮廓的点分布特征分析和识别步态   总被引:1,自引:0,他引:1  
提出了一种轮廓点分布特征匹配方法来分析和识别行人步态。首先通过设计一种轮廓采样点区域分布直方图分析了步态的周期性特征,提取了一个步态周期的帧图像轮廓;继而采用一种局部轮廓描述子得到帧图像轮廓的点分布直方图阵列作为轮廓特征、用轮廓点集间的Hausdorff距离结合动态时间规整技术求取测试序列和参考序列间的匹配相似度;最后通过分类实现了人体步态识别。在Soton步态数据库进行了实验,正确分类识别率最高达到90.27%。相关文献的对比分析表明:该方法的识别率有较大的提高,是有效的。  相似文献   

17.
The gait recognition is to recognize an individual based on the characteristics extracted from the gait image sequence. There are many researches for the gait recognition which use diverse kinds of information such as shape of gait silhouette, motion variation caused by walking, and so on. In general, shape information is more useful for recognition. However, shape information is influenced by a variety of factors, which degrade the recognition performance. Moreover, the information used in most of those studies might be able to be extracted after all of one or more sequences of the gait cycle are known. And it is also hard to discriminate the gait cycle from given gait sequences exactly by the online approach. In regard to these difficulties, we propose a novel gait recognition method based on the multilinear tensor analysis. To recognize the cyclic characteristic of gait without an exact division for the gait cycle, this paper’s propose is the method to form the accumulated silhouette and then describes those as the tensor. For the accumulated silhouette proposed by this paper, the image sequence of one gait cycle is divided into four sections in the training phase. However, discrimination for the gait cycle in the training phase is not directly related to the recognition phase, thus the online approach is possible. We first form the accumulated silhouettes for every individual using gait silhouettes within each section. And then, we represent these accumulated silhouettes as the tensor. Using a multilinear tensor analysis, we compute the core tensor which governs the interaction between factors organizing the original tensor, and then compose the basis to recognize the individual in the online recognition framework. Finally, we recognize the individual using the computation of similarity based on the Euclidean distance, which is more suitable to our method. We verify the superiority of the proposed approach via experiments with real gait sequences.  相似文献   

18.
基于自适应LBP人脸识别的身份验证   总被引:1,自引:0,他引:1  
提出了一种自适应LBP人脸识别算法用于进行身份认证。在身份特征录入阶段,首先采用Harr人脸级联分类器对人脸样本库进行人脸区域检测,并使用PCA方法对人脸区域进行降维处理;然后通过LBP二值模式的人脸识别算法提取人脸样本的特征值;最后通过LBP人脸训练生成人脸数据特征库。通过多场景人脸图像库和阈值队列,通过多阈值全组人脸匹配,建立人脸阈值特征库。在身份验证阶段,将登录用户人脸与人脸阈值特征库做粗粒度人脸LBP直方图匹配,确定当前最优的LBP阈值;然后将登录用户人脸与人脸数据特征库做LBP直方图匹配,通过匹配结果确定登录用户的系统权限。实验结果表明,在图像和视频模式下,基于自适应LBP人脸识别算法的身份验证具有很高的鲁棒性。  相似文献   

19.
在远程教育考试系统中,如何实时有效地验证考生身份非常重要。本文提出一种基于FR(Face Recognition)的远程考试身份验证系统,首先利用肤色信息检测人脸图像,经过预处理后提取特征点,然后通过与报名库中人脸图像进行几何特征比对,从而完成考生的身份验证。实验表明该系统具有较好的识别率,能有效地识别出考生信息。  相似文献   

20.
Most of the current computer systems authenticate a user’s identity only at the point of entry to the system (i.e., login). However, an effective authentication system includes continuous or frequent monitoring of the identity of a user already logged into a system to ensure the validity of the identity of the user throughout a session. Such a system is called a “continuous or active authentication system.” An authentication system equipped with such a security mechanism protects the system against certain attacks including session hijacking that can be performed later by a malicious user. The aim of this research is to advance the state-of-the-art of the user-active authentication research using keystroke dynamics. Through this research, we assess the performance and influence of various keystroke features on keystroke dynamics authentication systems. In particular, we investigate the performance of keystroke features on a subset of most frequently used English words. The performance of four features including key duration, flight time latency, diagraph time latency, and word total time duration are analyzed. A series of experiments is performed to measure the performance of each feature individually as well as the results from the combinations of these features. More specifically, four machine learning techniques are adapted for the purpose of assessing keystroke authentication schemes. The selected classification methods are Support Vector Machine (SVM), Linear Discriminate Classifier (LDC), K-Nearest Neighbors (K-NN), and Naive Bayesian (NB). Moreover, this research proposes a novel approach based on sequential change-point methods for early detection of an imposter in computer authentication without the needs for any modeling of users in advance, that is, no need for a-priori information regarding changes. The proposed approach based on sequential change-point methods provides the ability to detect the impostor in early stages of attacks. The study is performed and evaluated based on data collected for 28 users. The experimental results indicate that the word total time feature offers the best performance result among all four keystroke features, followed by diagraph time latency. Furthermore, the results of the experiments also show that the combination of features enhances the performance accuracy. In addition, the nearest neighbor method performs the best among the four machine learning techniques.  相似文献   

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