Petri网模型在电信结算系统中的应用

由于Petri网模型具有强大的描述离散事件系统的能力,电信综合结算系统采用了基于Petri网的系统模型,作为分析工作流模型的理论基础。讨论了结算系统优化求解模型和工作流Petri网模型。结算系统建立了全局流程管理机制,调度系统统筹管理任务、进程和资源等各方面要素,成功减少了计算机资源消耗,也使结算系统的监控、配置、操纵更加方便和智能。     

智能视频监控系统的关键技术

目前,视频监控系统已经广泛应用于道路、车站、银行、小区等公共场所．但是获取到的视频数据大部分只是作为事发后的证据记录．不具备监控系统进行现场实时视频分析的功能。因此,如何自动有效地对监测场景进行实时监控,对现有的视频监控系统提出了新的要求。智能视频监控是通过摄像头获取的视频对监控场景中的人和交通工具进行实时监测．并对它们的行为和发生的事件作出反应。从技术角度而言,智能视频监控问题的研究内容相当丰富．包括运动物体目标的检测、跟踪、     

智能化交通视频图像处理技术研究

简单概述了交通监控系统中涉及的视频图像处理技术的主要内容,包括目标检测、跟踪、行为理解与事件发掘等,并针对若干问题的解决展开了讨论,提出了一种基于注意机制的交通视频分析和多传感器融合监控框架,以提升视频智能化分析的主动性和实时性.     

有界Petri网等价性的判定算法

Petri网语言是系统行为分析的一种重要工具,为了分析有界Petri网的行为等价,借助于有限自动机的等价性问题和算法,研究了有界Petri网的等价性问题和算法.定义了带标注Petri网语言等价性,证明了带标注的有界Petri网到有限自动机的等价转化,给出了判定有界Petri网的等价性算法,为模拟系统的性能比较提供了处理方法.     

基于蚁群优化的时间Petri网及其在柔性制造系统调度优化中的应用

Petri网的优化调度求解主要采用基于状态空间的智能搜索方法,执行效率往往不高.提出基于蚁群优化的时间Petri网,通过在Petri网的变迁和进化规则中引入蚁群优化机制,改变Petri网原有的非确定性选择行为,使之具备蚁群寻优选择智能行为,克服了需要基于状态空间进行启发式搜索的缺陷,提高了调度优化的计算效率.最后应用蚁群优化时间Petri网模型,对柔性制造系统的区间Job Shop调度问题进行建模和优化求解.实验结果进一步验证了所提模型和方法的有效性.     

一种基于逻辑Petri网的过程挖掘方法

逻辑Petri网是抑制弧Petri网和高级Petri网的抽象和扩展,可在过程挖掘中简洁准确的表示活动之间复杂的业务逻辑关系.本文在传统Petri网挖掘方法的基础上,为了进一步提高复杂系统挖掘模型的简洁度和拟合度,尤其是对并行活动间存在复杂与或关系的系统,提出了一种基于逻辑Petri网的过程挖掘方法,并给出了逻辑Petri网中逻辑变迁的挖掘算法.它可以充分挖掘活动之间的业务逻辑,并且业务逻辑可用逻辑表达式表示.通过与相应Petri网模型的实例比较分析,例证了本文方法的正确性和有效性,且逻辑Petri网模型更加适合日志行为.     

基于广电网络的社会面监控视频传输系统方案

随着三网融合的不断推进,需要基于广电城域网和IP视频传输网络,建立一个完全基于广电宽带网的新型增值业务模式,通过网络化视频监控系统,对监控目标进行监视、控制、安全防范及智能管理,主要介绍丹阳市社会面视频监控系统的网络传输方案和主要功能。     

一种恶意软件实时检测模型

启发式扫描检测入侵行为未知的恶意软件,存在误报及漏报问题,且不能有效监控Rootkit。基于＂通过监控某种恶意行为,实现对一类入侵方式未知的恶意软件的实时检测＂的思想,提出了一种实时检测入侵行为未知恶意软件的Petri网模型,给出了性能测量及优化方法。通过在模型指导下建立的恶意软件实时检测系统中采集关键参数,完成了模型性能评价和调整。设计的系统可实时准确地检测具有特征行为的恶意软件。     

基于Petri网的入侵检测模型研究

随着计算机网络的广泛应用,非法的入侵与攻击行为不断发生,严重威胁着网络信息的安全,对入侵和攻击进行检测与防范已经成为刻不容缓的重要课题。讲述了Petri网(PN)和有色Petri网(CPN),通过将入侵分为“存在”,“顺序”,“偏序”三种类型,描述入侵检测系统(IDS)中的攻击模式用Petri网实现,并且给出了使用有色Petri网描述攻击模式。     

基于复杂校园环境的IP视频监控规划与设计研究

视频监控系统目前运用相当广泛,针对学校校园的复杂环境以及事件多发的情况,文章通过对传统模拟视频监控和IP视频监控对比的方法,采用系统性、可靠、智能化的IP视频监控设计方案解决传统模拟视频监控无法满足的问题。实现了IP视频监控系统对校园的安全防范,突发事件的及时响应,为事件的事后取证提供了保障。同时,阐述了智能化的视频监控技术,为学校的管理提供了便利。     

Intelligent Mobile Video Surveillance System with Multilevel Distillation

This paper proposes a mobile video surveillance system consisting of intelligent video analysis and mobile communication networking. This multilevel distillation approach helps mobile users monitor tremendous surveillance videos on demand through video streaming over mobile communication networks. The intelligent video analysis includes moving object detection/tracking and key frame selection which can browse useful video clips. The communication networking services, comprising video transcoding, multimedia messaging, and mobile video streaming, transmit surveillance information into mobile appliances. Moving object detection is achieved by background subtraction and particle filter tracking. Key frame selection, which aims to deliver an alarm to a mobile client using multimedia messaging service accompanied with an extracted clear frame, is reached by devising a weighted importance criterion considering object clarity and face appearance. Besides, a spatial-domain cascaded transcoder is developed to convert the filtered image sequence of detected objects into the mobile video streaming format. Experimental results show that the system can successfully detect all events of moving objects for a complex surveillance scene, choose very appropriate key frames for users, and transcode the images with a high power signal-to-noise ratio (PSNR).     

A hybrid algorithm for automatic segmentation of slowly moving objects

Segmentation of moving objects in video sequences is a basic task in many applications. However, it is still challenging due to the semantic gap between the low-level visual features and the high-level human interpretation of video semantics. Compared with segmentation of fast moving objects, accurate and perceptually consistent segmentation of slowly moving objects is more difficult. In this paper, a novel hybrid algorithm is proposed for segmentation of slowly moving objects in video sequence aiming to acquire perceptually consistent results. Firstly, the temporal information of the differences among multiple frames is employed to detect initial moving regions. Then, the Gaussian mixture model (GMM) is employed and an improved expectation maximization (EM) algorithm is introduced to segment a spatial image into homogeneous regions. Finally, the results of motion detection and spatial segmentation are fused to extract final moving objects. Experiments are conducted and provide convincing results.     

基于多帧边缘差异的视频运动对象的分割与跟踪算法

从视频场景中分割和跟踪感兴趣的视频对象对于MPEG-4等基于对象的视频编码来说是关键性的技术之一。针对目前大部分视频对象分割和追踪算法相当复杂但仍不能有效地去除背景噪声的问题,该文提出用于分割和跟踪视频运动对象的一种基于多帧边缘差异的算法。该算法利用一组帧的边缘差异来提取运动对象区域,通过聚类方法去除背景像素点,利用形态学算子得到对象分割模板,同时通过建立前帧感兴趣对象与当前帧运动对象的帧间向量跟踪当前帧的感兴趣视频对象。不同标准视频测试序列的测试结果表明,该算法能够实现对感兴趣的视频运动对象更为精确、快速和有效地分割和跟踪。     

Calculation of 3D trajectories of moving objects fromunsynchronised stereo video signals

A method for the 3D reconstruction of moving objects from unsynchronised stereo video signals is presented. Using a video mosaicing technique for each video signal, all frames are registered in a reference frame and the trajectories of moving objects obtained as a static structure in a scene, so that correspondence can be determined from an epipolar geometry     

CORBA规范的形式化描述及分析

CORBA为构建大规模分布式应用程序提供了一套公共对象服务规范,其规范主要以IDL语言编写,只提供对象的静态行为描述．提出并应用扩展有色Petri网对CORBA对象进行形式化模拟和分析,结果表明扩展有色Pctri网模型不仅能够清楚描述对象的静态行为,同时也能较好地模拟对象分布性和动态行为．     

Augmented keyframe

In surveillance applications, keyframes are usually used to summarize important video contents. However, most traditional keyframe extraction approaches just select some video frames from the input video, while the information in these selected video frames are insufficient and cannot let the users perceive the events happened in the original video easily. In this paper, we propose a novel keyframe generating technique to condense the contents of a surveillance video clip captured by a static camera into a still picture (augmented keyframe). The augmented keyframe is a more meaningful keyframe augmented with representative objects, important contents (human faces, license plate, etc.), motion status (represented as icons) and some marks of the moving objects in a still picture. This new technique consists of two major phases: content extraction and content synthesis. Some testing results of the proposed augmented keyframe are also presented and compared with results obtained by the traditional keyframe approach.     

A self-organizing approach to background subtraction for visual surveillance applications.

Detection of moving objects in video streams is the first relevant step of information extraction in many computer vision applications. Aside from the intrinsic usefulness of being able to segment video streams into moving and background components, detecting moving objects provides a focus of attention for recognition, classification, and activity analysis, making these later steps more efficient. We propose an approach based on self organization through artificial neural networks, widely applied in human image processing systems and more generally in cognitive science. The proposed approach can handle scenes containing moving backgrounds, gradual illumination variations and camouflage, has no bootstrapping limitations, can include into the background model shadows cast by moving objects, and achieves robust detection for different types of videos taken with stationary cameras. We compare our method with other modeling techniques and report experimental results, both in terms of detection accuracy and in terms of processing speed, for color video sequences that represent typical situations critical for video surveillance systems.     

一种基于IPC的多区域网络视频监控系统设计

针对多区域网络监控的应用需求,设计了一套基于IPC的网络化视频监控系统。该系统采用基于视频分析的运动目标侦测,基于双码流的图片、视频传输与存储,以及优先级和多通道的IPC与图片服务器交互等关键技术。由此,实现了多区域全时段的标清视频监控,实时运动检测报警与连续高清图片抓拍取证功能。该系统设计兼容现有的软硬件系统平台,并具有较高性价比。     

一种基于帧内图像分区的视频对象自动分割算法

视频运动对象的自动分割是实现新一代对象基视频编码标准MPEG-4的重要技术,本文提出了一种基于帧内图像分区的运动对象自动分割算法.首先以时域运动信息为依据利用高斯检验方法得到二值运动掩模图像,并建立MRF随机场模型进一步检验,然后提出了一种结合非线性变换的改进分水岭算法进行帧内图像分区,以划定对象区域与背景区域的界线,最后对时域分割和帧内分区结果进行比重运算,得到最终运动对象.针对MPEG-4标准测试序列和自采集手指视频序列的实验结果说明了算法的有效性.