基于极坐标的树木叶片特征提取方法

提出了一种在极坐标下进行特征提取的方法,并将其应用于树木叶片图像识别中。该方法首先将目标图像二值化并映射到极坐标下,提取具有旋转、缩放、平移不变性的曲线面积比率、跨度比、饱和度和高度变化率等特征。然后通过最小欧式距离对叶片进行计算、识别。该方法克服了直角坐标系下特征提取方法计算量大,花费的时间长的缺陷。基于该方法的叶片特征提取算法的时间复杂度为[O(n)]。对于叶型有区分,且需要快速进行树叶识别的树叶数据集有很好的效果。该方法在常见的13种树木叶片中进行测试,平均正确识别率达到90%以上。     

基于极坐标的改进灰度积分投影法的人眼检测

为了克服传统灰度积分投影方法无法有效定位旋转人脸图像中人眼的缺点,提出了一种基于极坐标系的灰度积分投影方法。利用肤色特征对给定图像进行人脸区域的确定,在人脸区域内按极角方向进行灰度积分投影,确定出人眼所在角度,将人眼角度方向的像素灰度值做水平方向积分投影,从而确定出人眼的位置。该方法能够实现同一幅图像中多个不同姿态人脸的人眼定位。大量的仿真实验表明,该方法的识别性能对人脸的旋转变化具有良好的鲁棒性,能够提高灰度积分投影方法对人眼定位的适用范围。     

一种基于极坐标的分布度保持策略

将极坐标的思想引入多目标遗传算法来保持解的多样性,由此提出了一种新的多目标遗传算法：PCGA2（Polar Coordinates Genetic AlgorithmsⅡ）;分析了基于极坐标的分布度保持策略的时间复杂度,并通过实验将PCGA2同当前流行的两种多目标遗传算法（NSGA2和SPEA2）进行了比较。实验数据表明该算法不仅在时间耗费上比较低,而且所得到的解具有非常好的分布度。     

一种极坐标下基于高斯过程的扩展目标跟踪方法

对于使用雷达系统的扩展目标跟踪,通常将原始测量值从极坐标转换为笛卡尔坐标,然后馈入估计器.但其转换测量期望值在目标真实方位上存在偏差.另外,测量误差协方差的计算取决于实践中不可用的真实状态.针对这一不足,本文提出了一种在概率数据关联框架下基于高斯过程的扩展目标跟踪方法.该方法首先,直接在极坐标中对测量函数进行建模,并求解出测量噪声协方差;其次,建立扩展目标的联合跟踪门对测量进行筛选,并获得测量新息;最后,计算关联事件概率并估计扩展目标的状态.仿真结果表明了该方法的有效性.     

A robust rotation resilient video watermarking scheme based on the SIFT

This paper proposes a blind and robust video watermarking algorithm for copyright protection of the video in the wavelet transform. The watermark bit is embedded by modifying two random high frequency coefficients in the first level discrete wavelet transform of the frames of the video. The watermark is encrypted before embedding by using the cat map for better security. During the watermark extraction phase, it is verified whether the video is attacked by rotation attack. Frame restoration against rotation attack is done based on matching at least two feature points each generated by the scale invariant feature transform in the original video frame and the watermarked one. The angle between the two lines formed by joining these feature points is used to restore the video frames to the original position. Experimental results show the imperceptibility and robustness of the proposed method against variety of attacks. It is especially robust against rotation attack in comparison with other popular watermarking methods. Normalized Correlation, Structural Similarity Index and Peak Signal-to-Noise-Ratio are nearly 100%, 1, above 48 dB respectively against the various attacks.     

Noise robust and rotation invariant texture classification based on local distribution transform

Multimedia Tools and Applications - Applying local binary pattern (LBP) to images with uniform distribution leads to generate discriminative features; however, the distribution of all images is not...     

WSN的极坐标最小能耗覆盖空洞修复算法

针对混合无线传感器网络中的覆盖空洞问题,提出了一种基于极坐标的空洞修复算法。首先,通过计算静态节点感知圆交叉点的位置确定空洞边界点,连接空洞边界点构造空洞多边形;其次,按照极坐标方法计算每个空洞多边形中的虚拟修复节点位置;最后,建立虚拟修复节点与移动节点之间的距离数据表,将表中移动节点移动到与之匹配的虚拟节点位置上,完成空洞修复。仿真结果表明,该算法能够有效判定并修复网络中的覆盖空洞,相比同类算法,所需移动修复节点数量较少,移动节点平均移动距离较短,在提高网络覆盖质量的同时延长了网络的生存周期。     

Median Fisher Discriminator: a robust feature extraction method with applications to biometrics

In existing Linear Discriminant Analysis (LDA) models, the class population mean is always estimated by the class sample average. In small sample size problems, such as face and palm recognition, however, the class sample average does not suffice to provide an accurate estimate of the class population mean based on a few of the given samples, particularly when there are outliers in the training set. To overcome this weakness, the class median vector is used to estimate the class population mean in LDA modeling. The class median vector has two advantages over the class sample average: (1) the class median (image) vector preserves useful details in the sample images, and (2) the class median vector is robust to outliers that exist in the training sample set. In addition, a weighting mechanism is adopted to refine the characterization of the within-class scatter so as to further improve the robustness of the proposed model. The proposed Median Fisher Discriminator (MFD) method was evaluated using the Yale and the AR face image databases and the PolyU (Polytechnic University) palmprint database. The experimental results demonstrated the robustness and effectiveness of the proposed method.     

A robust eye gaze tracking method based on a virtual eyeball model

Gaze positions can provide important cues for natural computer interfaces. In this paper, we describe a new gaze estimation method based on a three dimensional analysis of the human eye which can be used in head-mounted display (HMD) environments. This paper presents four advantages over previous works. First, in order to obtain accurate gaze positions, we used a virtual eyeball model based on the 3D characteristics of the human eyeball. Second, we calculated the 3D position of the virtual eyeball and gaze vector by using a camera and three collimated IR-LEDs. Third, three reference frames (the camera, the monitor and the eye reference frames) were unified, which simplified the complex 3D converting calculations and allowed for calculation of the 3D eye position and gaze position on a HMD monitor. Fourth, a simple user-dependent calibration method was proposed by gazing at one position based on Kappa compensation. Experimental results showed that the eye gaze estimation error of the proposed method was lower than 1°.

---

基于生物特征识别的门限身份认证方案

在传统生物特征身份认证系统中,针对重要目标的保护时,单一用户的身份认证方案存在用户权限过高的问题。为了解决此类问题,利用BGN半同态加密算法,结合Shamir秘密共享设计了一种基于生物特征识别的门限身份方案。主要使用在双线性对上BGN同态加密算法进行数据保护,利用第三方认证中心进行秘密分割,服务器在密文状态下对用户的身份进行认证,实现门限身份认证。通过性能分析验证了方案的安全性和高效性。     

弹道坐标中三维鲁棒非线性导引律

本文针对机动目标拦截问题,考虑导弹控制系统动态特性及其不确定性,利用分块反步设计思想,结合输入-状态稳定性理论,在弹道坐标系中设计了一种三维非线性鲁棒导引律.与大多数已有的导引律相比,本文直接地在弹道坐标系中设计导引律,并且所设计的导引律可有效克服控制系统动态特性和不确定性对制导效果的影响,理论分析和数值仿真表明,本文设计的导引律对目标机动和控制系统所受的外来有界扰动均具有较强的鲁棒性.     

基于生物特征的数字水印综述研究

生物信息学与信息安全具有高度互补性,用生物特征来确保信息安全已经成为国内外研究的热点.为此研究了利用生物特征来生成数字水印.介绍了数字水印技术所具有的安全性、隐蔽性和鲁棒性的基本特征,讨论了当前常用的水印嵌入算法,阐述了基于在线签名的生物特征数字水印生成过程,最后给出了基于生物特征的数字水印技术的应用和研究方向.     

Fusion of eye movement and mouse dynamics for reliable behavioral biometrics

This paper presents the first attempt to fuse two different kinds of behavioral biometrics: mouse dynamics and eye movement biometrics. Mouse dynamics were collected without any special equipment, while an affordable The Eye Tribe eye tracker was used to gather eye movement data at a frequency of 30 Hz, which is also potentially possible using a common web camera. We showed that a fusion of these techniques is quite natural and it is easy to prepare an experiment that collects both traits simultaneously. Moreover, the fusion of information from both signals gave 6.8 % equal error rate and 92.9 % accuracy for relatively short registration time (20 s on average). Achieving such results were possible using dissimilarity matrices based on dynamic time warping distance.     

改进证据理论的多生物特征融合方法

多生物特征融合考虑了个体的多种生理或行为特征,因而能显著地改善系统的识别性能,成为生物特征识别技术未来发展趋势之一。利用训练样本的识别率和误识率,提出了基于证据理论的多生物特征融合识别方法;对各识别专家的识别率和误识率进行分析,提出了一种基于累积频率和证据理论（Cumulative Frequency based D-S,CFDS）的多生物特征融合方法;通过几个实验证明了改进的D-S算法的有效性,提高了合成结果的可靠性。     

基于衍生多边形的混合坐标

将多边形三角化,利用三角网格将三角形衍生为点多边形、边多边形和面多边形,再根据已有的重心坐标提出基于衍生多边形的混合坐标.首先在三角网格内根据初始多边形内部一点所在的三角形得到衍生多边形,然后使用调和坐标、局部重心坐标、迭代坐标中任意一种计算衍生多边形的顶点关于初始多边形顶点的重心坐标,再使用迭代坐标计算初始多边形内部...     

Multi-instance cancellable biometrics schemes based on generative adversarial network

The main role of cancellable biometric schemes is to protect the privacy of the enrolled users. The protected biometric data are generated by applying a parametrized transformation function to the original biometric data. Although cancellable biometric schemes achieve high security levels, they may degrade the recognition accuracy. One of the mostwidely used approaches to enhance the recognition accuracy in biometric systems is to combine several instances of the same biometric modality. In this paper, two multi-instance cancellable biometric schemes based on iris traits are presented. The iris biometric trait is used in both schemes because of the reliability and stability of iris traits compared to the other biometric traits. A generative adversarial network (GAN) is used as a transformation function for the biometric features. The first scheme is based on a pre-transformation feature-level fusion, where the binary features of multiple instances are concatenated and inputted to the transformation phase. On the other hand, the second scheme is based on a post-transformation feature-level fusion, where each instance is separately inputted to the transformation phase. Experiments conducted on the CASIA Iris-V3-Internal database confirm the high recognition accuracy of the two proposed schemes. Moreover, the security of the proposed schemes is analyzed, and their robustness against two well-known types of attacks is proven.

     

基于生物特征和口令放大的远程认证协议

基于口令的认证协议具有简单、方便、强适应性及移动性等优点,它广泛应用于网上银行、ATM等远程登录环境中。但是一般用户的口令具有低熵、安全性低、口令数据难以保护等缺点,从而使系统存在许多安全隐患。口令放大是这样的一种算法,它输入用户的低熵的口令和一个高熵的随机数,然后输出一个高熵的新口令,从而提高了系统的安全性,也不增加用户的负担。人体生物特征是人体所固有的生理和行为特征,而模糊提取器可以从人体的生物特征中提取出高熵的随机串。生物特征和口令放大的结合,恰好可以克服基于口令的认证协议的缺点,提高其安全性。提出了一种结合人体生物特征和口令放大的单向认证协议,充分发挥了基于口令的认证协议所具有的简单易用和生物特征高熵、安全性高等优点,并且具有一定的容错能力。