基于 MSTP 传输的高清视讯会议系统

为了实现国－省－市3级广播电视安全播出指挥调度系统的互联互通,保证浙江省广播电视安全播出指挥调度、监测监管工作的开展,分析现有视讯会议系统的现状,对全省视讯会议系统基于MSTP传输的平台进行了升级和改造,升级后进一步提高了系统的可靠性,提升了调度指挥的协调能力,并将对全省广电系统开展培训、应对突发事件发挥重要作用。     

基于FPGA的视频与通讯数据融合设计

为实现将时间值、方位值等串口通讯信息叠加进数字视频图像信号的某一固定行中,设计了基于FPGA的通讯数据与数字视频数据的融合系统。采用FPGA程序设计实现串行数据接收与内置FIFO处理,并提取视频数据的某一固定行,进行数据融合,使得通讯数据和视频数据在场信号有效下组合输出。基于FPGA的通讯数据与数字视频数据的融合系统实现了通讯数据与视频数据的融合,试验中通讯数据波特率为230.4kbit/s,视频信号帧频50 Hz,视频数据与通讯数据帧频相同,图像像素为1 024×1 024,通讯数据正确的融合入一场图像的最后一行中,系统工作稳定,工作状态良好。基于FPGA的通讯数据与数字视频数据的融合系统以最简硬件系统实现了通讯数据与数字视频数据的组合输出,满足图像处理及显示系统的要求,具有广泛的工程意义。     

基于双边信息的分布式视频压缩感知模型研究

针对传统视频编码技术计算量大和复杂度高的缺点,提出一种基于双边信息的分布式视频压缩感知算法。该算法将压缩感知技术与分布式视频编码技术相结合,把视频序列分为Key帧和CS帧,Key帧运用传统的帧内编码和解码,CS帧编码端运用压缩感知编码,解码端运用视频块内与视频块间的双边信息和梯度投影算法进行优化重构。通过双边信息的运动估计和压缩编码器的设计,实现基于双边信息的分布式视频压缩感知模型的构建。仿真结果表明该模型既可以实现高效编码,又可以实现复杂度由编码端向解码端转移,在较低的采样率下,提高视频的压缩能力和传输速度。     

基于VLC的室内无线视频语音通信系统的设计和实现

提出了一种基于可见光通信技术的新型室内无线视频语音通信系统。本文介绍了相关的系统架构,全双工的实现技术及TCP/IP的组网方案等,并对室内可见光通信中提高系统整体性能的若干关键技术进行了讨论。     

基于分布式视频编码的低能耗视频传感器节点研究

在无线多媒体传感器网络中,如何提高节点能源的利用率,延长整个网络的生命周期是当前迫切需要解决的关键问题。从视频数据处理和传输能耗的角度出发,对分布式视频编码(DVC)基础理论及视频传感器节点的能耗模型进行分析和研究。通过实验仿真的方式将H.264帧内编码方案同DVC方案进行比较,实验结果表明了DISCOVER-DVC方案在节点节能方面的优势。最后基于DISCOVER-DVC算法,在S3C6410硬件平台和嵌入式Linux操作系统平台之上完成视频传感器节点设计,来降低节点能耗,提高节点生命周期。     

一种新型和差旁瓣抑制阵列天线

针对传统和差阵列天线旁瓣抑制能力的不足,设计了一种应用于二次雷达的新型和差旁瓣抑制阵列天线.该天线主要由前向阵列、后向单元、波束形成网络和互连的射频电缆构成,其中前向阵列和后向单元共同形成差波束.采用遗传算法对各个天线单元的幅度和相位进行优化,使差波束在工作频带内能够覆盖和波束的旁瓣.仿真和测试结果表明:在13.2％相...     

基于ARM9和GSM／GPRS的无线可移动红外监测报警系统

设计了一种基于ARM9（Advanced RISC Machines）和GSM（Global Systemfor Mobile Communications）／GPRS（General Packet Radio Service）网络的无线可移动红外监测报警系统,系统以嵌入式操作系统Linux2．6和ARM9核心的嵌入式处理器S3C2410作为软硬件核心,利用红外监测模块实现对目标物的监测,在GPRS网络中使用socket（套接字）编程技术和FTP协议将现场图像无线传输到服务器上,并在GSM网络中以短信息的方式向用户报警。系统的创新之处在于仅当红外监测模块探测到入侵障碍物时才进行现场图像的采集和传输并向用户报警,因此可以按流量计费以节省使用GPRS网络的费用。系统具有一定的通用性、可行性和高性价比,有一定的实用价值。     

Research on key thechnologies of pornographic image/video recognition in compressed domain

Pornographic image/video recognition plays a vital role in network information surveillance and management. In this paper, its key techniques, such as skin detection, key frame extraction, and classifier design, etc, are studied in compressed domain. A skin detection method based on data-mining in compressed domain is proposed firstly and achieves the higher detection accuracy as well as higher speed. Then, a cascade scheme of pornographic image recognition based on selective decision tree ensemble is proposed in order to improve both the speed and accuracy of recognition. A pornographic video oriented key frame extraction solution in compressed domain and an approach of pornographic video recognition are discussed respectively in the end.     

A supervised learning approach to automate the acquisition of knowledge in surveillance systems

This paper presents a machine learning-based method to build knowledge bases used to carry out surveillance tasks in environments monitored with video cameras. The method generates three sets of rules for each camera that allow to detect objects’ anomalous behaviours depending on three parameters: object class, object position, and object speed. To deal with uncertainty and vagueness inherent in video surveillance we make use of fuzzy logic. Thanks to this approach we are able to generate a set of rules highly interpretable by security experts. Besides, the simplicity of the surveillance system offers high efficiency and short response time. The process of building the knowledge base and how to apply the generated sets of fuzzy rules is described in depth for a real environment.     

Combining scene model and fusion for night video enhancement

This paper presents a video context enhancement method for night surveillance. The basic idea is to extract and fuse the meaningful information of video sequence captured from a fixed camera under different illuminations. A unique characteristic of the algorithm is to separate the image context into two classes and estimate them in different ways. One class contains basic surrounding scene information and scene model, which is obtained via background modeling and object tracking in daytime video sequence. The other class is extracted from nighttime video, including frequently moving region, high illumination region and high gradient region. The scene model and pixel-wise difference method are used to segment the three regions. A shift-invariant discrete wavelet based image fusion technique is used to integral all those context information in the final result. Experiment results demonstrate that the proposed approach can provide much more details and meaningful information for nighttime video.