Finger-vein image recognition combining modified hausdorff distance with minutiae feature matching

In this paper, we propose a novel method for finger-vein recognition. We extract the features of the vein patterns for recognition. Then, the minutiae features included bifurcation points and ending points are extracted from these vein patterns. These feature points are used as a geometric representation of the vein patterns shape. Finally, the modified Hausdorff distance algorithm is provided to evaluate the identifica-tion ability among all possible relative positions of the vein patterns shape. This algorithm has been widely used for comparing point sets or edge maps since it does not require point cor-respondence. Experimental results show these minutiae feature points can be used to perform personal verification tasks as a geometric rep-resentation of the vein patterns shape. Fur-thermore, in this developed method. we can achieve robust image matching under different lighting conditions.

A modified image matching algorithm based on robust Hausdorff distance

Hausdorff distance measure is one of the widely adopted feature-based image matching algorithms due to its simplicity and accuracy.However,it is considered that its robustness still needs to be improved.In this paper,various forms of original and improved Hausdorff distance(HD) and their limitations are studied.Focusing on robust Hausdorff distance(RHD),an improved RHD with an adaptive outlier point threshold selection method is proposed.Furthermore,another new form of the Hausdorff distance which possesses the merits of RHD and M-HD is prsented.Finally,a recursive algorithm is introduced to accelerate the image matching speed of Hausdorff algorithms.Extensive simulation and experiment results are presented to validate the feasibility of the proposed Hausdorff distance algorithm.

Time-Domain Protection for Transmission Lines Connected to Wind Power Plant based on Model Matching and Hausdorff Distance

The system impedance instability,high-order harmonics,and frequency offset are main fault characteristics of wind power system.Moreover,the measurement angle of faulty phase is affected by rotation speed frequency component,which causes traditional directional protections based on angle comparison between voltage and current to operate incorrectly.In this paper,a time-domain protection for connected to wind power plant based on model matching is proposed,which compares the calculated current and the measured current to identify internal faults and external faults.Under external faults,the calculated current and measured current waveform are quite similar because the protected transmission lines is equivalent to a lumped parameter model and the model itself is not damaged.However,the similarity of calculated current and measured current is quite low,due to destroyed integrity of model under internal faults.Additionally,Hausdorff distance is introduced to obtain the similarity of the calculated current and measured current.Since the proposed protection scheme is applied in time domain,it is independent from current frequency offsets of wind energy system,high-order harmonics,and system impedance variations.Comprehensive case studies are undertaken through Power Systems Computer Aided Design(PSCAD),while simulation results verify the accuracy and efficiency of the proposed approach in fault identification.

Measuring Musical Rhythm Similarity: Further Experiments with the Many-to-Many Minimum-Weight Matching Distance

Musical rhythms are represented as sequences of symbols. The sequences may be composed of binary symbols denoting either silent or monophonic sounded pulses, or ternary symbols denoting silent pulses and two types of sounded pulses made up of low-pitched (dum) and high-pitched (tak) sounds. Experiments are described that compare the effectiveness of the many-to-many minimum-weight matching between two sequences to serve as a measure of similarity that correlates well with human judgements of rhythm similarity. This measure is also compared to the often used edit distance and to the one-to-one minimum-weight matching. New results are reported from experiments performed with three widely different datasets of real- world and artificially generated musical rhythms (including Afro-Cuban rhythms), and compared with results previously reported with a dataset of Middle Eastern dum-tak rhythms.

A New Robust Image Matching Method Based on Distance Reciprocal

Object matching between two-dimensional images is an important problem in computer vision. The purpose of object matching is to decide the similarity between two objects. A new robust image matching method based on distance reciprocal was presented. The distance reciprocal is based on human visual perception. This method is simple and effective. Moreover, it is robust against noise. The experiments show that this method outperforms the Hausdorff distance, when the images with noise interfered need to be recognized.

Topological distance-constrained feature descriptor learning model for vessel matching in coronary angiographies

Background Feature matching technology is vital to establish the association between virtual and real objects in virtual reality and augmented reality systems.Specifically,it provides them with the ability to match a dynamic scene.Many image matching methods,of which most are deep learning-based,have been proposed over the past few decades.However,vessel fracture,stenosis,artifacts,high background noise,and uneven vessel gray-scale make vessel matching in coronary angiography extremely difficult.Traditional matching methods perform poorly in this regard.Methods In this study,a topological distance-constrained feature descriptor learning model is proposed.This model regards the topology of the vasculature as the connection relationship of the centerline.The topological distance combines the geodesic distance between the input patches and constrains the descriptor network by maximizing the feature difference between connected and unconnected patches to obtain more useful potential feature relationships.Results Matching patches of different sequences of angiographic images are generated for the experiments.The matching accuracy and stability of the proposed method is superior to those of the existing models.Conclusions The proposed method solves the problem of matching coronary angiographies by generating a topological distance-constrained feature descriptor.

Chamfer Matching在CT和MRI图像匹配融合中的应用

医学影像中的CT和MRI图像的精确匹配融合能为临床提供全面、丰富的诊断信息。文中首先对CT图像正常脑组织边缘做距离变换 ,形成距离图像 ,然后利用MRI图像正常脑组织边缘作为模板 ,实现了CT和MRI图像的精确匹配。在此基础上完成了CT和MRI的信息融合。文中算法适用于CT和MRI的匹配 ,并对SPECT ,PET 。

2D registration based on contour matching for partial matching images

The mean Hausdorff distance, though highly applicable in image registration, does not work well on partial matching images. An improvement upon traditional Hausdorff-distance-based image registration method is proposed, which consists of the following two aspects. One is to estimate transformation parameters between two images from the distributions of geometric property differences instead of establishing explicit feature correspondences. This procedure is treated as the pre-registration. The other aspect is that mean Hausdorff distance computation is replaced with the analysis of the second difference of generalized Hausdorff distance so as to eliminate the redundant points. Experimental results show that our registration method outperforms the method based on mean Hausdorff distance. The registration errors are noticeably reduced in the partial matching images.

基于统计局部特征描述与匹配的点云配准算法

针对ICP算法在初始位姿差、部分数据丢失和噪声干扰情况下鲁棒性差、配准精度低的问题,提出一种基于统计局部特征描述与匹配的点云配准算法。首先,用点云局部密度、点云拟合平面距离方差、高斯曲率和平均曲率构建一个四维的统计局部特征描述符,准确地描述查询点的局部特征;然后,通过点对间的特征差异进行对应点匹配,剔除错误点对,解决点云部分数据缺失和噪声干扰的问题;最后,使用平均匹配距离作为度量改进ICP算法,对点云进行配准,解决初始位姿较差时配准精度低的问题。实验结果表明,该算法在初始位姿差、部分数据丢失和噪声干扰情况下的配准精度提高至少1个量级,配准速率也有较大提升,在鲁棒性和配准精度方面均表现出明显优势。

基于PCA算法的人脸匹配技术研究

基于PCA算法的人脸匹配是一种常见的计算机视觉技术,主要应用于人脸图像的分类和匹配任务。利用PCA技术对人脸图像进行特征提取和降维处理,将人脸分为测试集和训练集,然后用欧式距离计算测试集中选择的图像和训练集中所有图像的距离,选择距离最短的图像作为人脸匹配结果。实验采集了200张不同拍摄角度和不同表情的人脸图像,对待匹配的人脸图像加入不同程度噪声进行人脸匹配,实验结果显示基于PCA算法的人脸匹配技术,完成匹配的平均时间为1.2494s,人脸图像匹配准确率为97.25%。

多模态异构大数据混合属性特征匹配筛选算法

多模态异构大数据混合了多种属性数据,具有数据类型繁杂、数据维度较高的特点,在数据挖掘过程中容易降低多模态异构大数据利用率。为了提高特征匹配紧密度,提出多模态异构大数据混合属性特征匹配筛选算法。建立距离矩阵对多模态异构大数据实施混合属性降维;采用主成分分析法提取降维后的数据主成分,将提取到的主成分作为数据混合属性备选特征;计算主成分互信息,筛选互信息值大于1的数据特征,聚集同属性相似特征,实现特征匹配。在4个多模态异构大数据集中进行应用测试,测试结果表明所提算法匹配紧密度均高于0.8,由此证明,该算法具有较高的混合属性特征匹配质量。

利用改进的Hausdorff距离匹配多尺度线要素

传统Hausdorff距离对噪声较敏感,在进行多尺度线要素匹配时,易导致漏匹配和误匹配。为提高匹配正确率,提出了一种改进的Hausdorff距离算法。针对部分匹配问题,采用曲线分割算法,以短曲线分割长曲线;针对点位分布差异问题,采用曲线加密算法,以匹配曲线的中间节点进行双向加密;针对曲线点集自身的噪声问题,以距离集合的中位数作为相似性指标,判断匹配要素是否为同名要素。选取不同尺度的行政区划界线和道路网数据进行匹配,以验证该算法。结果表明,该算法具有较好的匹配效果。

融合知识图谱和语义匹配的医疗问答系统

问答系统是自然语言处理领域中的一项重要任务,常应用于医疗服务。传统的问答系统通过知识图谱的实体关系匹配返回相应的尾实体作为答案,然而,倘若实体或关系无法识别,又或者在知识图谱中并不存在相应的实体关系,问答将无法继续进行。为了解决这一问题,建立一种融合知识图谱和语义匹配模型的中文医疗问答混合系统。当所提问题无法在知识图谱中进行实体关系匹配时,该模型能继续从问答对数据集中找到最相似的问题,并返回相应结果作为答案。在语义匹配模型方面,结合中文医疗相似问题对,在Sentence-BERT模型上进行微调训练,并引入双曲空间中的距离度量函数对句子对进行相似度度量。结果表明:在整体性能方面,所提模型相较于BERT这类大语言模型精度能提升7.16%;在度量能力方面,双曲度量相较于通用欧氏空间度量,如余弦度量,最高能有2.28%的精度提升和1.58%的F_1值提升。

Lower Bounds of Distance Laplacian Spectral Radii of n-Vertex Graphs in Terms of Fractional Matching Number

A fractional matching of a graph G is a function f: E(G)→[0,1] such that for each vertex v, ∑eϵΓG(v)f(e)≤1.. The fractional matching number of G is the maximum value of ∑e∈E(G)f(e) over all fractional matchings f. Tian et al. (Linear Algebra Appl 506:579–587, 2016) determined the extremal graphs with minimum distance Laplacian spectral radius among n-vertex graphs with given matching number. However, a natural problem is left open: among all n-vertex graphs with given fractional matching number, how about the lower bound of their distance Laplacian spectral radii and which graphs minimize the distance Laplacian spectral radii? In this paper, we solve these problems completely.

增程式电动汽车动力系统参数匹配建模仿真分析

增程式电动汽车是以纯电能驱动的车辆,通过动力蓄电池和一个小型的增程器(Auxiliary Power Unit)为车辆提供电能,在增加了车辆续航里程的同时,工况适应性也随之提高,被评为目前具有较高研发前景的新能源汽车[1]。本文以城市SUV车型的增程式电动汽车为需求目标进行研究。根据整车参数及制定的控制策略,基于AVL Cruise软件为平台建立性能仿真模型;建立Simulink控制策略模型;分别在短途行驶模式和长途行驶模式下选定符合相应模式的行驶工况进行联合仿真分析。结果表明,整车动力性及续航里程均能达到初始的设计目标,为增程式电动汽车的技术拓展和多样的控制策略提供可行性方案。

改进型Code-Matched交织器

Turbo码作为信道编码方案 ,可以获得较高的误比特率 (BER)性能 ,而交织器的设计是影响Turbo码性能的关键环节 .笔者在码的重量分析的基础上提出了一种改进型Code Matched交织器 ,它可以减少低重量码的数量 ,从而提高Turbo码的性能 .这种改进型Code Matched交织器可以适用于多种不同生成矩阵产生的Turbo码 ,而且不会影响Turbo码在中、高信噪比处的性能 ,同时 ,在Rayleigh信道下 。

An Intelligent Graph Edit Distance-Based Approach for Finding Business Process Similarities

There are numerous application areas of computing similarity between process models.It includes finding similar models from a repository,controlling redundancy of process models,and finding corresponding activities between a pair of process models.The similarity between two process models is computed based on their similarity between labels,structures,and execution behaviors.Several attempts have been made to develop similarity techniques between activity labels,as well as their execution behavior.However,a notable problem with the process model similarity is that two process models can also be similar if there is a structural variation between them.However,neither a benchmark dataset exists for the structural similarity between process models nor there exist an effective technique to compute structural similarity.To that end,we have developed a large collection of process models in which structural changes are handcrafted while preserving the semantics of the models.Furthermore,we have used a machine learning-based approach to compute the similarity between a pair of process models having structural and label differences.Finally,we have evaluated the proposed approach using our generated collection of process models.

A WGN和衰落信道下具有改进型Code-matched交织器的Turbo码(英文)

提出了一种改进型的Code Matched交织器,它能减少低重量码的数量,从而提高Turbo码的性能。这种改进型的Code Matched交织器可以适用于多种不同生成矩阵产生的Turbo码,而且不会影响Turbo码在中高信噪比处的性能。同时,在Rayleigh信道下,这种交织器能降低错误平台。