A two-layer fuzzy pattern matching procedure for the evaluation of conditions involving vague quantifiers

In this note, we are interested in the evaluation of conditions of the form The value of attribute a for Q items of X is in F or more shortly Q items of X are F, where X is a set of items, Q denotes a possibly vague proportion (which may be linguistically expressed, e.g. most), F is a (possibly fuzzy) subset of the attribute domain of a. and where the available knowledge about the value a(x) of the attribute a for any item x may be imprecise or even vague. The evaluation is based on a fuzzy pattern matching procedure repeated two times. Such conditions may be encountered in queries addressed to an incomplete information data base or in the if-part of expert rules.     

Film and television industry cloud exhibition design based on 3D imaging and virtual reality

The three-dimensional virtual scene can provide users with a visual three-dimensional virtual environment, with various multimedia channels such as sound, video, force feedback equipment, etc., to bring users a completely immersive interactive experience. This paper introduces 3D imaging and virtual reality technology in the film and television industry cloud exhibition, and develops a virtual display platform. First of all, this paper divides the registration into two processes: camera calibration and joint calibration of the camera and laser scanner based on the calibration results. Camera calibration can determine the plane model of the calibration board in the camera coordinate system, and the joint calibration uses the RANSAC algorithm to extract the point cloud of the plane model of the calibration board, and then optimizes the distance between the points in the plane model point cloud and the corresponding plane in the camera coordinate system Find the optimal transformation between the two sets of data, and then calculate the registration relationship between the point cloud and the image. Secondly, this article conducts a demand analysis of the film and television industry cloud exhibition platform based on virtual reality technology, including the business goals set by the platform, platform system analysis, overall design, and system operating environment and configuration requirements. This model provides a feasible solution for the visual interaction of the cloud exhibition design of the film and television industry.     

基于ARM的QNMV指纹识别系统的研究

目前指纹识别技术正向着嵌入式和小型化的方向发展,搭建了基于ARM的指纹识别系统的硬件平台并对硬件进行了优化,研究了指纹识别的软件开发环境,给出了指纹识别系统的软件实现方框图和详细的指纹识别算法流程图;详细论述了全新的基于QNMV结构向量的指纹匹配算法,给出了算法优化后的一些测试数据,将指纹匹配算法与其他常见的算法进行了数据比对后,发现系统具有较好的性能指标:具有较低的误识率(FAR)和拒识率(FRR)、识别率(MRI)有了较大的提高、有效地缩短了匹配耗费时间(Time-Match);系统具有安全可靠、易于扩展、性价比高等优点。     

SVM-based ontology matching approach

There are a lot of heterogeneous ontologies in semantic web, and the task of ontology mapping is to find their semantic relationship. There are integrated methods that only simply combine the similarity values which are used in current multi-strategy ontology mapping. The semantic information is not included in them and a lot of manual intervention is also needed, so it leads to that some factual mapping relations are missed. Addressing this issue, the work presented in this paper puts forward an ontology matching approach, which uses multi-strategy mapping technique to carry on similarity iterative computation and explores both linguistic and structural similarity. Our approach takes different similarities into one whole, as a similarity cube. By cutting operation, similarity vectors are obtained, which form the similarity space, and by this way, mapping discovery can be converted into binary classification. Support vector machine (SVM) has good generalization ability and can obtain best compromise between complexity of model and learning capability when solving small samples and the nonlinear problem. Because of the said reason, we employ SVM in our approach. For making full use of the information of ontology, our implementation and experimental results used a common dataset to demonstrate the effectiveness of the mapping approach. It ensures the recall ration while improving the quality of mapping results.     

角点距离矩阵和同心圆划分的曲线描述与匹配

曲线匹配对于物体识别、目标跟踪、碎片拼接等有着重要的意义。针对曲线匹配的效率与鲁棒性问题,提出了一种基于角点距离矩阵和同心圆划分的曲线描述与匹配算法。该算法分为粗略匹配和精确匹配两个阶段。粗略匹配阶段首先采用角点距离矩阵来描述曲线;然后通过子矩阵的方法来匹配曲线。精确匹配阶段首先采用同心圆划分的方法描述曲线;然后通过两条曲线同心圆描述集的差异度度量函数来度量他们的相似性。算法不仅具有平移、旋转、缩放不变性,而且具有较强的鲁棒性,可用于遮挡物体的匹配以及基于轮廓的图形拼接。实验结果表明了该算法的有效性和可行性。     

均衡化特征匹配的非刚体细胞形态跟踪

提出利用均衡化特征匹配来进行非刚性细胞形体跟踪的方法。采用重启动的随机游走方法建立并求解特征匹配概率模型,利用双向均衡方法对匹配邻接矩阵进行均衡化处理,得到指定目标与待跟踪目标之间的精确匹配,以获得目标的定位跟踪结果。同时利用特征匹配结果进行目标的自动标定,并应用图像分割方法进行目标的精确轮廓跟踪。实验结果表明,将该方法应用于视频中动态背景下的运动细胞形态跟踪时,在背景相似度较高及目标迅速移动的条件下,表现出了良好的性能,与同类方法相比可获得较高的定位精度以及更为准确的目标轮廓。     

分段线性动态矩匹配条带去除

由于探测器之间对接收的地物辐射信号的响应特征不同,导致遥感数据含有条带噪声,严重影响了图像质量及后续的定量计算。针对探测器响应函数在图像低值区及高值区呈非线性的特点,在着重分析矩匹配方法的基础上,提出分段线性动态矩匹配条带去除方法。方法设定阈值分割高中低值域统计区间,对探测器响应函数进行分段线性拟合,并对探测器每一分图像动态采用其领域内均值和标准差作为参考值进行条带纠正。应用TM数据第4波段及环境一号卫星高光谱数据进行去条带实验,并定性和定量地比较了该方法与动态矩匹配、傅里叶变换、自动均衡化曲线方法的去条带效果。结果表明该方法能够在保留图像基本信息的前提下,获得最佳的去条带效果,尤其能够提高非均匀地物分布区域内水体的条带去除效果。     

实时系统安全评估机制及其仿真研究

研究了嵌入式实时系统弹性应对策略中的安全评估机制。工业控制系统中存在嵌入系统,现有嵌入式系统无法动态掌握系统运行时的安全状况并无法做出响应的问题。为了保证嵌入系统安全运行,提出了实时系统的弹性应对策略以改善系统的安全性,设计并实现了模式匹配的嵌入式实时系统安全等级评估模块,可以实现动态实时的系统安全状况评价,并为系统动态配置安全策略提供了决策支持。采用RT-Linux建立了仿真评估环境,对安全等级评估系统的性能进行了仿真测试。测试结果表明安全等级评估模块的系统开销很小,能够有效的保障嵌入式实时系统的安全运行,具有广泛的应用价值和前景。