Filterbank-based fingerprint matching

Biometrics-based verification, especially fingerprint-based identification, is receiving a lot of attention. There are two major shortcomings of the traditional approaches to fingerprint representation. For a considerable fraction of population, the representations based on explicit detection of complete ridge structures in the fingerprint are difficult to extract automatically. The widely used minutiae-based representation does not utilize a significant component of the rich discriminatory information available in the fingerprints. Local ridge structures cannot be completely characterized by minutiae. Further, minutiae-based matching has difficulty in quickly matching two fingerprint images containing a different number of unregistered minutiae points. The proposed filter-based algorithm uses a bank of Gabor filters to capture both local and global details in a fingerprint as a compact fixed length FingerCode. The fingerprint matching is based on the Euclidean distance between the two corresponding FingerCodes and hence is extremely fast. We are able to achieve a verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms published in the open literature. Our system performs better than a state-of-the-art minutiae-based system when the performance requirement of the application system does not demand a very low false acceptance rate. Finally, we show that the matching performance can be improved by combining the decisions of the matchers based on complementary (minutiae-based and filter-based) fingerprint information.     

网上考试系统中指纹验证模块的研究与算法实现

网上考试中运用指纹认证方法,可以有效地杜绝代考现象的发生.文中探讨了网上指纹验证过程中的算法实现,综合运用图像处理和模式识别技术,研究了指纹识别的理论和技术,建立了一对一的指纹识别系统.整个系统框架采用浏览器/服务器(B/S)结构,用户在客户端提交指纹图像,而服务器端则完成指纹图像的预处理、匹配算法等,再将识别信息反馈给客户端.     

Balancing performance factors in multisource biometric processing platforms

It is generally recognised that no one biometric data source or processing platform is universally appropriate for optimising performance across all problem domains. Multibiometric processors, which combine identity information obtained from more than one biometric source are commonly promoted as optimal structures for maximising performance, and much research has been carried out to investigate appropriate strategies for combining the available information. However, the techniques of multiclassifier pattern recognition also offer opportunities to improve the performance of systems operating within a unimodal environment, yet such solutions have been less extensively investigated in the specific case of biometric applications. This study presents an empirical study of the relations between these two different approaches to enhancing the performance indicators delivered by biometric systems. In particular we are interested to increase our understanding of the relative merits of, on the one hand, multiclassifier/single modality systems and, on the other, full multibiometric configurations. We focus our study on three modalities, the fingerprint and hand geometry (two physiological biometrics) and the handwritten signature (a behavioural biometric).     

Image quality and position variability assessment in minutiae-based fingerprint verification

The assessment of a complete minutiae-based fingerprint automatic verification system, when degrading variability factors are included, is presented. A new large public fingerprint database, the so-called MCYT Fingerprint Database, is used to evaluate the performance of the system in verification tasks. The design of this database, in terms of controlled variability in fingerprint positioning, has made it possible to determine the system performance when the test or the stored images are subject to changes in fingerprint core placing. Some procedures are proposed to cope with this problem, including a multiple-reference strategy. Human supervision and labelling of the image quality of the acquired fingerprint images has also been accomplished, permitting a precise assessment of the proposed minutiae extraction and pattern matching processes. Results, including enhanced procedures for both position variability control and image quality consideration, are presented in terms of DET plots, leading to highly competitive verification scores in terms of EER (equal error rate).     

轻量化多特征融合的指纹分类算法研究

快速准确的指纹分类在大型指纹识别系统中是加速目标指纹查找的关键技术。目前,指纹分类算法存在复杂度高、操作繁琐、参数较多、所需数据规模大、且无法充分利用指纹特征信息等问题。神经网络深层提取的特征更加关键,也更有代表性,但忽略了部分浅层信息。针对指纹分类存在的问题,本文提出一种轻量化多特征融合的指纹分类算法。该算法设计了轻量化Finger-SqueezeNet来训练指纹图像,采用查表法求得指纹的细化图之后,利用改进的分布求和梯度法求取相应细化图的感兴趣区域(Region Of Interest,ROI)图像;将指纹ROI图像输入网络深层与提取的特征图进行特征融合,使得深层网络也能获得浅层中纹线准确的走向信息,从而增强网络对于纹型的敏感度;采用Maxout激活函数对网络提取的特征进行激活。实验结果表明,本文算法不仅减少了训练参数量,而且通过指纹ROI图像补偿深层特征图,更加充分利用了指纹的纹型信息,轻量化算法也可为指纹分类模型拓展到移动端提供理论支撑。      

Human identification using finger images

This paper presents a new approach to improve the performance of finger-vein identification systems presented in the literature. The proposed system simultaneously acquires the finger-vein and low-resolution fingerprint images and combines these two evidences using a novel score-level combination strategy. We examine the previously proposed finger-vein identification approaches and develop a new approach that illustrates it superiority over prior published efforts. The utility of low-resolution fingerprint images acquired from a webcam is examined to ascertain the matching performance from such images. We develop and investigate two new score-level combinations, i.e., holistic and nonlinear fusion, and comparatively evaluate them with more popular score-level fusion approaches to ascertain their effectiveness in the proposed system. The rigorous experimental results presented on the database of 6264 images from 156 subjects illustrate significant improvement in the performance, i.e., both from the authentication and recognition experiments.     

A broad-band wide-angle scan matching technique for large environmentally restricted phase arrays

Numerical solutions for the problem of radiation from an infinite planar array of waveguide horns loaded at the aperture with a thick partially dielectric filled inductive step plus an external radome are presented. The analysis is applied to the problem of matching a practical array over a specified scan volume and frequency band. A technique from which the best possible initial match is obtained by varying the step width and thickness is presented. The final broad-band match is obtained with the aid of two thin capacitive irises located inside the waveguides. Experimental verification of the analysis and resultant computer program used for the design is presented in the form of waveguide simulator results. ThreeH-plane simulators are used and comparison of theory and experiment is presented for different combinations of external and internal matching structures.     

指纹的脊频率估计

本文提出了一种新的指纹图像脊频率的估计方法。该方法通过给定的模板对指纹采样信号卷积，增强了信号峰值，抑制了噪声，从而还原出指纹的脊谷结构，提高了指纹脊频率估计的精确性，有利于指纹识别时的其他后续操作。实验结果表明，与以往的一些脊频率估计算法相比，在精确性和及时性方面，本文所提出的方法用来估计脊频率有明显的优势，更适合于在线指纹识别系统。     

Vulcan--A versatile high-power glass laser for multiuser experiments

This paper reports the design and characterization of the newly upgraded Nd:glass laser facility at the Rutherford Laboratory. Emphasis is placed on the unusual aspects consequent on its role as a multiuser facility, where reliability and flexibility are of paramount importance. The basic facility configuration is of two high-power laser systems in parallel-a six-beam laser for implosion experiments and a separate high-power single beamline for either X-ray backlighting diagnostics of implosion experiments or use in a separate single-beam target area. Additional flexibility is provided by remotely controlled changeover mirrors enabling groups of amplifiers to be used in different combinations for various energies and shot repetition rates. Either a mode-locked or aQ-switched oscillator can be selected to provide a range of pulse durations from 50 ps to many nanoseconds. Harmonic generation is used routinely to give a choice of wavelengths for different experiments. The six-beam system is normally run at the second harmonic, although the fundamental wavelength is also available, while the single-beam target area can use fundamental, second, or third harmonics.     

全光纤光学相干层析系统用于人造指纹的识别

目前商用指纹识别系统由于仅依赖于手指表面二 维图像的脊模式和细节特征进行识别,对人造 指纹有极大的安全漏洞。本文提出一种利用光学相干层析(OCT)技术识别 人造指纹的方法。在分析OCT系统原理及皮肤光学特性的基础上,使用研制的全光纤OCT系 统分别对 人体手指以及被商用指纹识别系统识别通过的人造指模进行成像,获得了二者的二维OCT图 像和对应的一 维信号,同时获得人造指模的三维OCT图像,通过对比分析二者深度方向 上的微结构信息 以及光学特性可以准确地识别出人造指模。实验结果表明,OCT技术不仅可以用于指纹的防 伪,有效地提高生物特征识别系统的安全性能,而且还具有用于指纹识别的潜力。     

Magnetic energy-based feature extraction for low-quality fingerprint images

In fingerprint recognition systems, feature extraction is an important part because of its impact on the final performance of the overall system, particularly, in the case of low-quality images, which poses significant challenges to traditional fingerprint feature extraction methods. In this work, we make two major contributions: First, a novel feature extraction method for low-quality fingerprints images is proposed, which mimics the magnetic energy when attracting iron fillings, and this method is based on image energies attracting uniformly distributed points to form the final features that can describe a fingerprint. Second, we created a new low-quality fingerprints image database to evaluate the proposed method. We used a mobile phone camera to capture the fingerprints of 136 different persons, with five samples for each to obtain 680 fingerprint images in total. To match the computed features, we used the dynamic time warping and evaluated the performance of our system based on k-nearest neighbor classifier. Further, we represent the features using their probability density functions to evaluate the method using some other classifiers. The highest identification accuracy recorded by several experiments reached 95.11% using our in-house database. The experimental results show that the proposed method can be used as a general feature extraction method for other applications.     

Design trade-offs in cellular/PCS systems

With the increasing demand for all kinds of wireless access services, including cellular/PCS, wireless local loop, and broadband access, the system architects will have opportunities to design new communication systems, not necessarily based on existing wireless standards. In the design of wireless communication systems, there are usually multiple objectives such as low cost, small size, high reliability, and large capacity. The system architect would need to study the trade-offs among different combinations of modulation, coding, multiple access, and antenna techniques to determine the best design. In this tutorial we focus on the trade-offs between user bandwidth and multi-user interference in order to maximize the system capacity. The design trade-offs are depicted on a B-γ₀ plane. Where B is the user bandwidth and γ₀ is the carrier-to-interference ratio (C/I). For F/TDMA and CDMA systems, the author first shows that the contours of equal system capacity are straight lines with different slope's depending on the propagation environment, and the capacity decreases for increasing B and γ₀. Then as feasible solutions, the author plots the different combinations of modulation and coding with diversity to satisfy a certain quality of service in a multipath environment. The best design is obtained by moving a line with a certain slope from the lower left corner in the B-γ₀ plane until it touches the first feasible solution. From these plots we can see that, for example, while 1/2-rate channel coding is the best choice for F/TDMA systems, 1/3-rate is better for CDMA systems     

On the Performance of Space–Time Block-Coded MIMO Video Communications

The problem of efficient video communications over multiple-input-multiple-output (MIMO) wireless systems is of great significance due to the high capacity of the multiple antenna system. The high data rates provided by the MIMO system can be traded off with diversity gain by using different channel-coding schemes. Also, by using different video source-coding methods, high compression gain can be traded off with the error resilience gain. One should jointly consider source coding and channel coding when designing a MIMO wireless video system. However, little is known so far about what combinations of channel-coding and source-coding methods have the best overall performance in a MIMO system. In this paper, by comparing the performances of several different typical combinations through both theoretical and simulation studies, we show that no single combination is the best for the entire range of channel conditions, but rather, different combinations may be best for a subrange     

Score bi-Gaussian equalisation for multimodal person verification

Multimodal biometric fusion at score level can be performed by means of combinatory or classificatory techniques. In the first case, it is straightforward that the normalisation of the scores is a very important issue for the success of the fusion process. In the classificatory approach as, for instance, in support vector machine (SVM)- based systems, only simple normalisation methods are usually applied. In this work, histogram equalisation of biometric score distribution is successfully applied in a multimodal person verification system composed by prosodic, speech spectrum and face information. Furthermore, a new bi-Gaussian equalisation (BGEQ) is introduced, which takes into account the separate statistics of the genuine and impostor scores by using as a reference a sum of two Gaussian functions, whose standard deviations model the overlap between the genuine and impostor lobes of the original distributions. Multimodal verification experiments are shown, where prosodic and speech spectrum scores are provided by speech experts using the Switchboard-I database, and face scores are obtained by a face recognition expert using XM2VTS database. BGEQ in combination with an SVM fusion system with a polynomial kernel has obtained the best results and has outperformed in more than a 21.29% the results obtained by min?max normalisation.     

用于梳状结构光学测速系统的周期优化方法

为了提高梳状结构光学测速系统的测速精度,采用数学原理研究了梳状结构的间距大小对输出光强信号周期性的影响,通过优化输出光强信号的周期性来提高测速精度,并采用一种结合图像处理选择最佳间距的实验方法,进行了相关的理论分析,对两种不同路面进行了实验仿真验证,得到不同间距下不同的输出光强信号的周期性情况。结果表明,当栅状结构的间距大小与地面特征点大小一致时,得到的输出光强周期性最优,对于普通的柏油和水泥路面,对应到地面的最佳栅状结构间距大小为1.0mm ~1.5mm。     

Personal identification using feature and score level fusion of palm- and fingerprints

The ever increasing demand of security has resulted in wide use of Biometric systems. Despite overcoming the traditional verification problems, the unimodal systems suffer from various challenges like intra class variation, noise in the sensor data etc, affecting the system performance. These problems are effectively handled by multimodal systems. In this paper, we present multimodal approach for palm- and fingerprints by feature level and score level fusions (sum and product rules). The proposed multi-modal systems are tested on a developed database consisting of 440 palm- and fingerprints each of 55 individuals. In feature level fusion, directional energy-based feature vectors of palm- and fingerprint identifiers are combined to form joint feature vector that is subsequently used to identify the individual using a distance classifier. In score level fusion, the matching scores of individual classifiers are fused by sum and product rules. Receiver operating characteristics curves are formed for unimodal and multimodal systems. Equal Error Rate (EER) of 0.538% for feature level fusion shows best performance compared to score level fusion of 0.6141 and 0.5482% of sum and product rules, respectively. Multimodal systems, however, significantly outperform unimodal palm- and fingerprints identifiers with EER of 2.822 and 2.553%, respectively.     

Formal Verification of Analog and Mixed Signal Designs Using SPICE Circuit Simulation Traces

Analog and Mixed Signal (AMS) designs can be formally modeled as hybrid systems [45] and therefore formal verification techniques applicable to hybrid systems can be deployed to verify them. An extension to a formal verification approach applicable to hybrid systems is proposed to verify AMS designs [31]. In this approach formal verification (FV) is carried out on an AMS block using simulation traces from SPICE, a simulator widely used in the design and verification of analog and AMS blocks. A broader implication of this approach is the ability to carry out hierarchical verification using relevant simulation traces obtained at different abstraction levels of a design when modeled in appropriate platforms. This enables a seamless transition of design and verification artifacts from the highest level of abstraction to the lowest level of implementation at the transistor level of any AMS design and a resulting increase in confidence on the correctness of the final implementation. The proposed approach has been justified with its applications to different AMS design blocks. For each design, its formal model and the proposed computational techniques have been incorporated into CheckMate [11] - a FV tool for hybrid systems based on MATLAB and the Simulink/Stateflow framework from MathWorks. A further justification of the proposed approach is the resulting improvements observed in terms of reduced verification time for different specifications in each design.     

CAEFi:基于卷积自编码器降维的信道状态信息指纹室内定位方法

针对提高Wi-Fi指纹室内定位技术性能,该文首先提出一种基于卷积神经网络(CNN)的信道状态信息(CSI)指纹室内定位方法。该方法在离线阶段联合CSI幅度差和相位差信息对CNN模型进行训练。在廊厅和实验室两种不同室内定位场景进行了定位实验,分别获得了25 cm和48 cm的平均定位误差;然后,在此基础上重点针对提高基于CNN的CSI室内定位时效性,引入卷积自编码器(CAE)实现CSI的降维处理,在保证原始定位方法精度的前提下,定位时间提高了40%,同时将内存消耗降低到原算法的1/15,实验结果验证了所提算法的有效性。     

Fingerprint classification based on learned features

In this paper, we present a fingerprint classification approach based on a novel feature-learning algorithm. Unlike current research for fingerprint classification that generally uses well defined meaningful features, our approach is based on Genetic Programming (GP), which learns to discover composite operators and features that are evolved from combinations of primitive image processing operations. Our experimental results show that our approach can find good composite operators to effectively extract useful features. Using a Bayesian classifier, without rejecting any fingerprints from the NIST-4 database, the correct rates for 4- and 5-class classification are 93.3% and 91.6%, respectively, which compare favorably with other published research and are one of the best results published to date.     

Statistical fingerprint‐based intrusion detection system (SF‐IDS)

Intrusion detection systems (IDS) are systems aimed at analyzing and detecting security problems. The IDS may be structured into misuse and anomaly detection. The former are often signature/rule IDS that detect malicious software by inspecting the content of packets or files looking for a “signature” labeling malware. They are often very efficient, but their drawback stands in the weakness of the information to check (eg, the signature), which may be quickly dated, and in the computation time because each packet or file needs to be inspected. The IDS based on anomaly detection and, in particular, on statistical analysis have been originated to bypass the mentioned problems. Instead of inspecting packets, each traffic flow is observed so getting a statistical characterization, which represents the fingerprint of the flow. This paper introduces a statistical analysis based intrusion detection system, which, after extracting the statistical fingerprint, uses machine learning classifiers to decide whether a flow is affected by malware or not. A large set of tests is presented. The obtained results allow selecting the best classifiers and show the performance of a decision maker that exploits the decisions of a bank of classifiers acting in parallel.