您好,欢迎来到中国测试科技资讯平台!

首页> 《中国测试》期刊 >本期导读>改进式背景差分算法研究

改进式背景差分算法研究

2562    2016-01-18

免费

全文售价

作者:罗志伟1, 邵明亮1, 王昌荣2

作者单位:1. 厦门理工学院机械工程系, 福建 厦门 361024;
2. 厦门市特种设备检验检测院, 福建 厦门 361004


关键词:DSP芯片; 视频监控; 背景差分法; 动态权值


摘要:

该文提出一种改进式背景差分算法,并应用于监控系统中。针对人流量较少的监控情况,提出一种基于计算机视觉的嵌入式监控系统解决方案,其以DSP DM642为核心处理芯片,可对3路视频视角同时处理。系统利用动态权值的改进式背景差分算法对视频流进行实时监控,若发现异常事件,则自动存储一段时间的视频数据,并利用H.264压缩后保存至外存中以供事后取证。由于监控算法巧妙,普通的SD卡即可替代传统的硬盘,系统精简,使用方便。试验表明:该系统灵敏度可调,非常适用于外景和内景的库房监控。


Research and application of improved background difference algorithm

LUO Zhi-wei1, SHAO Ming-liang1, WANG Chang-rong2

1. Department of Mechanical Engineering, Xiamen University of Technology, Xiamen 361024, China;
2. Xiamen Institute of Special Equipment Inspection, Xiamen 361004, China

Abstract: In this work, a kind of improved background difference algorithm is put forward and applied in the monitoring system. A novel embedded monitoring system based on computer vision is presented to build simple and intelligent monitoring platform for less population flow. DSP DM642 is used as the core processing chip, which can process three video views at the same time. The improved background difference method based on dynamic weight is utilized to perform real-time monitor to the video. When the accident is discovered, the system would capture a section of video automatically, then H.264 compression algorithm is used to compress the video data and the video data is saved in the external memory as evidence. Thanks to ingenious surveillance algorithm, the traditional hard disk can be replaced by the SD card. Furthermore, the monitoring system is a simple and easy process. The experimental results show that system sensitivity is adjustable, and this system is suitable for out-door and in-door warehouse monitoring.

Keywords: digital signal processor(DSP); video monitoring; background image difference; dynamic weight

2014, 40(2): 1-4  收稿日期: 2013-7-15;收到修改稿日期: 2013-9-21

基金项目: 福建省教育厅A类项目(JA13237);国家自然科学基金青年基金项目(51105321);厦门市科技计划项目(3502Z20113037)

作者简介: 罗志伟(1979-),男,福建龙岩市人,副教授,硕士,研究方向为机电一体化技术。

参考文献

[1] Gupte S, Masound O, Martin RFK. Detection and classification for vehicles[J]. IEEE Transactions on Intelligent Transportation Systems,2002,3(1):37-47.
[2] Barron J L, Fleet D J, Beauchemin S S. Performance of optical flow techniques[J]. International Journal of Computer Vision,1994,12(1):43-77.
[3] Meier T, Ngun K N. Video segmentation for content-based coding[J]. IEEE Transactions on Circuits and Systems for Video Technology,1999,9(8):1190-1203.
[4] 张会敏,卢兰涛,崔鹏,等. 双阈值背景差分算法在嵌入式报警系统中的应用[J]. 传感器与微系统,2010,29(10):138-140.
[5] 朱明旱,罗大庸,曹倩霞. 帧间差分与背景差分相融合的运动目标检测算法[J]. 计算机测量与控制,2005,13(3):215-217.
[6] 朱明旱,罗大庸. 基于帧间差分背景模型的运动物体检测与跟踪[J]. 计算机测量与控制,2006,14(8):1004-1009.
[7] 陈凤东,洪炳镕. 基于动态阈值背景差分算法的目标检测方法[J]. 哈尔滨工业大学学报,2005,37(7):883-955.
[8] Foresti G L. A real-time system for video surveillance of unattended outdoor environments[J]. IEEE Transactions On Circuits and Systems for Video Technology,1998,8(6):697-704.
[9] 张圣强,王建军,顶蕾. 选煤厂智能视频监控中的运动人体目标检测方法[J]. 工矿自动化,2011(11):60-62.