生物特征识别学科发展报告

从手机解锁、小区门禁到餐厅吃饭、超市收银,再到高铁进站、机场安检以及医院看病,人脸、虹膜和指纹等生物特征已成为人们进入万物互联世界的数字身份证。生物特征识别赋予机器自动探测、捕获、处理、分析和识别数字化生理或行为信号的高级智能,是一个典型而又复杂的模式识别问题,一直处于人工智能技术发展前沿,在新一代人工智能规划、“互联网+”行动计划等国家战略中具有重要地位。由于生物特征识别涉及公众利益攸关的隐私、道德和法律等问题,近期也引起了广泛的社会关注。本文系统综述了生物特征识别学科发展现状、新兴方向、存在问题和可行思路,深入梳理了人脸、虹膜、指纹、掌纹、静脉、声纹、步态、行人重识别以及多模态融合识别的研究进展,以人脸为例重点介绍了生物特征识别领域近些年受到关注的新方向——对抗攻击和防御、深度伪造和反伪造,最后剖析总结了生物特征识别领域存在的3大挑战问题——“感知盲区”、“决策误区”和“安全红区”。本文认为必须变革和创新生物特征的传感、认知和安全机制,才有可能取得复杂场景生物识别学术研究和技术应用的根本性突破,破除现有生物识别技术的弊端,朝着“可感”、“可知”和“可信”的新一代生物特征识别总体目标发展。     

粗定位和协同表示的高光谱图像异常检测

目的 由于在军事和民用应用中的重要作用,高光谱遥感影像异常检测在过去的20~30年里一直都是备受关注的研究热点。然而,考虑到异常点往往藏匿于大量的背景像元之中,且只占据很少的数量,给精确检测带来了不小的挑战。针对此问题,基于异常点往往表现在高频的细节区域这一前提,本文提出了一种基于异常点粗定位和协同表示的高光谱遥感影像异常检测算法。方法 对输入的原始高光谱遥感影像进行空间维的降质操作;通过衡量降质后影像与原始影像在空间维的差异,粗略定位可能的异常点位置;将粗定位的异常点位置用于指导像元间的协同表示以重构像元;通过衡量重构像元与原始像元的差异,从而进一步优化异常检测结果。结果 在4个数据集上与6种方法进行了实验对比。对于San Diego数据集,次优算法和本文算法分别取得的AUC （area under curve）值为0.978 6和0.994 0;对于HYDICE （hyperspectral digital image collection equipment）数据集,次优算法和本文算法的AUC值为0.993 6和0.998 5;对于Honghu数据集,次优算法和本文方法的AUC值分别为0.999 2和0.999 3;对Grand Isle数据集而言,尽管本文方法以0.001的差距略低于性能第1的算法,但从目视结果图中可见,本文方法所产生的虚警目标远少于性能第1的算法。结论 本文所提出的粗定位和协同表示的高光谱异常检测算法,综合考虑了高光谱遥感影像的谱间特性,同时还利用了其空间特性以及空间信息的先验分布,从而获得异常检测结果的提升。     

多尺度超像素分割和奇异谱分析的高光谱影像分类

目的 高光谱影像（hyperspectral image,HSI）中“同物异谱,异物同谱”的现象普遍存在,使分类结果存在严重的椒盐噪声问题。HSI中的空间地物结构复杂多样,单一尺度的空间特征提取方法无法有效地表达地物类间差异和区分地物边界。有效解决光谱混淆和空间尺度问题是提高分类精度的关键。方法 结合多尺度超像素和奇异谱分析,提出一种新的高光谱影像分类方法,从而充分挖掘地物的局部空间特征和光谱特征,解决空间尺度和光谱混淆的问题,提高分类精度。利用多尺度超像素对影像进行分割,获取不同尺度的分割影像,同时在分割区域内进行均值滤波,减少类内的光谱差异,增强类间的光谱差异;对每个区域计算平均光谱向量,并利用奇异谱分析方法获取光谱的主要鉴别特征,同时消除噪声的影响;利用支持向量机对不同尺度超像素分割影像进行分类,并进行决策融合,得到最终的分类结果。结果 实验选取了两个标准高光谱数据集和一个真实数据集,结果表明,利用本文算法提取的光谱—空间特征进行分类,比直接在原始数据上进行分类分别提高约26.8%、9.2%和13%的精度;与先进的深度学习SSRN （spectral-spatial residual network）算法相比,本文算法在精度上分别提升约5.2%、0.7%和4%,并且运行时间仅为前者的18.3%、45.4%和62.1%,处理效率更高。此外,在训练样本有限的情况下,两个标准数据集的样本分别为1%和0.2%时,本文算法均能取得87%以上的分类精度。结论 针对高光谱影像分类中的难题,提出一种新的融合光谱和多尺度空间特征的HSI分类方法。实验结果表明,本文方法优于对比方法,可以产生更精细的分类结果。     

ARINC653实时任务可调度性验证方法

针对综合模块化航空电子系统(Integrated Modular Avionics,IMA)存在周期任务和非周期任务,以及任务间依赖关系,传统方法不能准确验证其实时任务可调度性的问题,本文提出了一种基于Stopwatch时间自动机的ARINC653实时任务可调度性验证方法,利用模型检验工具UPPAAL对IMA系统进行建模仿真,并结合统计模型检验(Statistical Model Checking,SMC)与符号模型检验(Symbolic Model Checking,MC)来验证其可调度性。实验结果表明,该方法不仅快速验证了IMA系统的可调度性,而且能够准确定位不可调度任务。     

A novel NMF-based authentication scheme for encrypted speech in cloud computing

Multimedia Tools and Applications - Authentication of encrypted speeches is a technique that can judge the integrity of encrypted speech in cloud computing, even the encrypted speeches have been...     

A symmetric image encryption scheme based on hybrid analog-digital chaotic system and parameter selection mechanism

In recent years, various chaos-based image encryption algorithms have been proposed to meet the growing demand for real-time secure image transmission. However, chaotic system that is the core component of chaos-based cryptosystem usually degrades under finite computing precision, causing many security issues. In this paper, a novel cryptosystem with analog-digital hybrid chaotic model is proposed. Firstly, the analog Chen chaotic system and the digital Logistic map are adopted to depict the capability of the hybrid model, in which analog system is used to perturb digital system. Dynamic analyses demonstrate that the hybrid method has better complexity, larger chaotic parameter range and good ability to counteract dynamical degradation. The chaos-based key streams generated by the perturbed Logistic map are more suitable for image encryption. Secondly, a parameter selection mechanism is introduced to increase security. The state variables of Chen chaotic system and cipher image are involved in parameter selection process to dynamically change the parameter of the perturbed Logistic map. The involvement of cipher image makes the key streams relevant to plain image and can resist known/chosen-plaintext attacks. Performance, security and comparison analyses indicate that this cryptosystem has high security, low time complexity, and ability to resist common attacks.

     

Broadband high‐gain slot grid array antenna for millimeter wave applications

A broadband high‐gain slot grid array antenna (SGAA) is proposed in this paper. Based on the electromagnetic complementarity principle, the metal elements in the traditional microstrip grid array antenna (GAA) are replaced by a wide slot element. Compared with the GAA, the proposed SGAA achieves broadband and high‐gain performance. In order to demonstrate this concept, a prototype with 9‐element SGAA is designed using wide slot radiation elements and fabricated on Rogers 5880 printed circuit board (PCB) substrates, which is fed by a 50 Ω coaxial probe. The measured and simulated results show a good agreement. The proposed SGAA achieves a measured peak gain of 14.8 dBi at 26.0 GHz, a 10‐dB impedance bandwidth from 22.2 to 28.5 GHz with a fractional bandwidth of 24.9%. These results indicate that the SGAA is with high performance and it is suitable for the fifth‐generation (5G) millimeter wave (mmW) wireless communication system.     

A simplification method for capacitance models in AlGaN/GaN high electron mobility transistors under large drain voltage using channel analysis

This article analyzes the bias dependence of gate‐drain capacitance (C_gd) and gate‐source capacitance (C_gs) in the AlGaN/GaN high electron mobility transistors under a high drain‐to‐source voltage (V_ds) from the perspective of channel shape variation, and further simplifies C_gd and C_gs to be gate‐to‐source voltage (V_gs) dependent only at high V_ds. This method can significantly reduce the number of parameters to be fitted in C_gd and C_gs and therefore lower the difficulty of model development. The Angelov capacitance models are chosen for verifying the effectiveness of simplification. Good agreement between simulated and measured small‐signal S‐parameters, large‐signal power sweep, and power contours comprehensively proves the accuracy of this simplification method.     

A lossless secret image sharing scheme using a larger finite field

Recent research has made an effort to take 8b-bit value as a polynomial coefficient and use a random number as the maximum coefficient term in a Shamir’s polynomial, where b > 0. These can help improve computationl efficiency by reducing the sum of calculating polynomials, and avoid the case of the coefficient of x^k??1 being zero. However, such research still has the issues of requiring much extra storage space, lossy secret image, shadow images with large size, and storing permutation key. To solve the above issues, in this paper, we propose a novel scheme which takes 8b-bit value as a polynomial coefficient, designs a bit-level method and runs under Galois Field GF(2^8b). Experimental results show that this scheme improves existing similar schemes on several aspects, such as less extra storage space and higher computational performance.

     

三维点云模型特征张量描述符的构造及自相似性分析

三维模型局部自相似性是物体形状分析中的一个基本问题,其中,局部形状描述符的构建对自相似性分析的最终结果至关重要.针对此问题,提出了一种基于张量融合特征描述符的自相似性分析方法.首先利用相关面和反向点对点云模型进行形状直径函数(shapediameterfunction,SDF)的近似计算;然后利用谱聚类对模型进行过分割成模型子块,由K近邻(K-nearest neighbor, KNN)邻域点的SDF、形状指数(shape index, SI)和高斯曲率(Gauss curvature,GS)矩阵构造三维特征张量;最后利用张量范数构造映射得到形状描述符,并定义相似性度量分析模型子块之间的自相似性.对几种最新的方法(包括部分匹配和显著性检测)进行了实验,无论是直观视觉效果,还是相似性测度和相对误差上的评价指标,结果均表明,该方法可有效地对形状进行描述,提高了点云模型相似子块的识别精度.