基于SOPC的智能视频监控技术研究
摘要
随着科学技术的发展与公共安全保障需求的提高,智能视频监控系统在工业生产、日常生活、警备与军事方面的应用越来越广泛。迫切的军用和民用需求,推动着智能视频监控技术持续而迅猛的发展。视频监控的常规方案是通过专用采集卡实现图像采集再由计算机处理应用的方法,但是由于成本、体积等多方面的约束难以得到广泛的实际研究与应用,因而设计一种轻便小巧的视频监控系统成为市场所需。
本文分析了智能视频监控系统的现状,比较FPGA、DSP和ARM三种芯片作为图像采集处理系统核心芯片的优缺点,结合项目背景和应用需求,提出了基于SOPC的视频图像输入与移动目标检测的实现方案,并对整个方案进行了深入研究。在该方案中各个外围芯片的配置和控制都由FPGA的逻辑实现,而对于移动目标的监控算法处理交给由NiosⅡ完成。为了满足FPGA中逻辑与NiosⅡ之间的通讯,编写了可以将NiosⅡ和控制逻辑无缝连接的符合Avalon总线规范的IP核,从而构造一个片上可编程系统。
另外,在智能视频监控系统中,移动目标的检测是基础保证,本文在研究了几种常用的运动目标检测算法,并分析它们各自的优缺点,选取了易于实现的减背景法。再根据减背景法的特点,研究了背景提取和背景更新的问题,提出了解决方案,在NiosⅡIDE中编程实现,并下载到硬件系统中进行验证,为进一步的深入研究奠定了基础。
本文将SOPC应用到整个智能视频监控设计中,具有成本低、扩展性好、携带方便及适用范围广等优点,发展前景十分广阔。
With the development of science and technology and the increasing demand of public security, the intelligent monitoring system is more and more widely used in the field of industrial production, daily life, police and military affairs. The badly demand of military and civilian use of the digital video technology promotes its continuous and rapid development. Generally the images are collected by specialized image acquisition card and then processed by computer. However, because of its high costs and size, it is hard to get the extensive practical research and application, so it is necessary to design a kind of portable video surveillance system for the market.
The paper introduces current state of intelligent video surveillance systems. By comparing the merits and demerits of FPGA, DSP and ARM as the core chip of the systems separately and considering the background and demands of the system, the paper puts forward the whole scheme of intelligent video surveillance technology based on SOPC. In this scheme, control logic module of peripheral interface, chips control logic module are all implemented by FPGA, and the moving object detection algorithms are realized by NiosⅡ. In order to satisfy the communication between the logic and Nios II, the paper compiles a IP core with Avalon bus, through which Nios II and peripheral device and users logic will seamlessly connect, to construct a chip programmable system.
In addition, in the system of intelligent video surveillance, moving targets detection is the basic guarantee. In the paper, several moving object detection algorithms frequently-used are introduced. And by analyzing their respective advantages and disadvantages, the paper selects the subtraction background method which is easy to be realized. According to the characteristics of the subtraction background method, the paper studies the method of background extraction and background updating, proposes solutions, which is realized in Nios II IDE and downloaded to the hardware system for verification, and lay the foundation for further.
In this paper, SOPC is applied to the entire intelligent video surveillance design with the advantages such as lower cost, good extension, convenience in carrying and wide range of applications, etc. Its development prospect is undoubtedly very bright.
本文分析了智能视频监控系统的现状,比较FPGA、DSP和ARM三种芯片作为图像采集处理系统核心芯片的优缺点,结合项目背景和应用需求,提出了基于SOPC的视频图像输入与移动目标检测的实现方案,并对整个方案进行了深入研究。在该方案中各个外围芯片的配置和控制都由FPGA的逻辑实现,而对于移动目标的监控算法处理交给由NiosⅡ完成。为了满足FPGA中逻辑与NiosⅡ之间的通讯,编写了可以将NiosⅡ和控制逻辑无缝连接的符合Avalon总线规范的IP核,从而构造一个片上可编程系统。
另外,在智能视频监控系统中,移动目标的检测是基础保证,本文在研究了几种常用的运动目标检测算法,并分析它们各自的优缺点,选取了易于实现的减背景法。再根据减背景法的特点,研究了背景提取和背景更新的问题,提出了解决方案,在NiosⅡIDE中编程实现,并下载到硬件系统中进行验证,为进一步的深入研究奠定了基础。
本文将SOPC应用到整个智能视频监控设计中,具有成本低、扩展性好、携带方便及适用范围广等优点,发展前景十分广阔。
With the development of science and technology and the increasing demand of public security, the intelligent monitoring system is more and more widely used in the field of industrial production, daily life, police and military affairs. The badly demand of military and civilian use of the digital video technology promotes its continuous and rapid development. Generally the images are collected by specialized image acquisition card and then processed by computer. However, because of its high costs and size, it is hard to get the extensive practical research and application, so it is necessary to design a kind of portable video surveillance system for the market.
The paper introduces current state of intelligent video surveillance systems. By comparing the merits and demerits of FPGA, DSP and ARM as the core chip of the systems separately and considering the background and demands of the system, the paper puts forward the whole scheme of intelligent video surveillance technology based on SOPC. In this scheme, control logic module of peripheral interface, chips control logic module are all implemented by FPGA, and the moving object detection algorithms are realized by NiosⅡ. In order to satisfy the communication between the logic and Nios II, the paper compiles a IP core with Avalon bus, through which Nios II and peripheral device and users logic will seamlessly connect, to construct a chip programmable system.
In addition, in the system of intelligent video surveillance, moving targets detection is the basic guarantee. In the paper, several moving object detection algorithms frequently-used are introduced. And by analyzing their respective advantages and disadvantages, the paper selects the subtraction background method which is easy to be realized. According to the characteristics of the subtraction background method, the paper studies the method of background extraction and background updating, proposes solutions, which is realized in Nios II IDE and downloaded to the hardware system for verification, and lay the foundation for further.
In this paper, SOPC is applied to the entire intelligent video surveillance design with the advantages such as lower cost, good extension, convenience in carrying and wide range of applications, etc. Its development prospect is undoubtedly very bright.
引文
[1]商婷婷.基于Nios Ⅱ软核处理器的网络化视频监控系统的研究[D].哈尔滨：哈尔滨理工大学,2008.
[2]唐晓燕.基于SOPC的图像采集和处理系统的设计与实现[D].北京：华北电力大学,2007.
[3]潘曦.基于SOPC的数字视频信号加密系统设计[D].南京：南京航空航天大学,2007
[4]徐力,孔岩.视频监控系统的现状和发展趋势[J].信息技术与信息化,2005,(4)：60-61.
[5]杨磊.全数字网络视频监控系统的技术发展趋势[J].金卡工程,2005,(1)：78-79.
[6]旭东,张培仁,高修峰.嵌入式网络视频监控系统仪表技术与传感器[J].2006,(8)：24-26.
[7]李兰英.Nios Ⅱ嵌入式软核SOPC设计原理及应用[M].北京：北京航空航天大学出版社,2006.
[8]陈丽.基于Nios Ⅱ的视频图像处理系统设计[D].北京：北京交通大学,2006.
[9]Altera. Nios Ⅱ Software Developer's handbook[EB/OL].2006.
[10]任爱锋,初秀琴.基于FPGA的嵌入式系统设计[M].西安：西安电子科技大学出版社,2004.
[11]王诚,吴继华,等.Altera FPGA/CPLD设计(高级篇)[M].北京：人民邮电出版社,2005.
[12]Altera Corporation. Introduction to QuartusⅡ Manual[EB], Apr 2005.
[13]于宗光,魏敬和,王国章.SOC和FPGA技术未来的发展趋势[J].电子与封装,2006,3(6)：3-4.
[14]周立功等.SOPC嵌入式系统基础教程[M].北京：北京航空航天大学出版社,2006.11.
[15]李秀娟,刘宪伟.基于Nios Ⅱ的SOPC系统开发与应用[J].电子技术,2007(3)：57-58.
[16]Nios Ⅱ Processor Reference Handbook. Altera Corporation[EB],2003.
[17]Nios Ⅱ Hardware Development Tutorial. Altera Corporation[EB],2005.
[18]Nios Ⅱ Software Developer's Handbook. AItera Corporation[EB],2005.
[19]Altrea Corp. Avalon Bus Specification Reference Manual[EB],2004.
[20]李明.基于SOPC的网络视频监控系统的设计与实现[D].大连：大连理工大学,2006.
[21]黄智伟,王彦,陈琼,潘礼,黄松.FPGA系统设计与实践[M].北京：电子工业出版杜,2005.
[22]蔡伟纲.Nios Ⅱ软件架构解析[M].西安：西安电子科技大学出版社,2007.
[23]裴建茹,李伟.基于Nios Ⅱ的嵌入式网络视频监控系统设计[J].视频应用与工程,2008,(2)：91-92.
[24]孙德印.基于彩色CMOS图像传感器的彩电白场光色检测系统[D].杭州：浙江大学光电工程学院,2003.
[25]OmniVision, OV7660 Single Chip CMOS VGA Color Digital Camera OmniVision Technologies[EB], Inc,2005.
[26]王建校,危建国.SOPC设计基础与实践[M].西安：西安电子科技大学出版社,2006.
[27]Altera Corporation. Cyclone FPGA Family Data Sheet[EB], March 2003.
[28]Altera. Cyclone Ⅱ FPGA Family[EB],2003.
[29]周立功等.SOPC嵌入式系统实验教程[M].北京：北京航空航天大学出版社,2006.11.
[30]池水明.FPGA在实时图像预处理中的应用[J].山两电子技术,2007,5,17-18.
[31]OmniVision Technologies Seril Camera Control Bus(SCCB) Specification[EB],2002.3.
[32]Whut_wj. OV7620/OV6620图像采集之深入探讨[EB],2006.4.
[33]吕鹏.基于FPGA的数字视频侦察监控系统设计[D].南京：南京理工大学,2009.
[34]于海,樊晓桠.基于FPGA异步FIFO的研究与实现[J].微电子学与计算机,2007,24(3)：210-216.
[35]赵效民.高手进阶,终极内存技术指南——完整／进阶版[J].电脑高手,2002,12.
[36]吴厚航.深入浅出玩转FPGA[M].北京：北京航空航天大学出版社,2010.
[37]Avalon Memory Mapped Interface Specification. Altera Corporation[EB]. Nov 2006.
[38]张瑞娟.基于视频图像的运动目标检测与跟踪算法研究[D].大连：大连理工大学,2008.
[39]王勇.基于统计方法的运动目标检测与跟踪技术研究[D].湖北：华中科技大学,2009.
[40]HOU Z, HAN C. A background reconstruction algorithm based on pixel intensity Classification[J]. Journal of Software,2005,16(9):1568-1576 (in Chinese)
[41]于成忠,朱骏,袁晓辉.基于背景差法的运动目标检测[J].东南大学学报,2005,(11)：160-161.
[2]唐晓燕.基于SOPC的图像采集和处理系统的设计与实现[D].北京：华北电力大学,2007.
[3]潘曦.基于SOPC的数字视频信号加密系统设计[D].南京：南京航空航天大学,2007
[4]徐力,孔岩.视频监控系统的现状和发展趋势[J].信息技术与信息化,2005,(4)：60-61.
[5]杨磊.全数字网络视频监控系统的技术发展趋势[J].金卡工程,2005,(1)：78-79.
[6]旭东,张培仁,高修峰.嵌入式网络视频监控系统仪表技术与传感器[J].2006,(8)：24-26.
[7]李兰英.Nios Ⅱ嵌入式软核SOPC设计原理及应用[M].北京：北京航空航天大学出版社,2006.
[8]陈丽.基于Nios Ⅱ的视频图像处理系统设计[D].北京：北京交通大学,2006.
[9]Altera. Nios Ⅱ Software Developer's handbook[EB/OL].2006.
[10]任爱锋,初秀琴.基于FPGA的嵌入式系统设计[M].西安：西安电子科技大学出版社,2004.
[11]王诚,吴继华,等.Altera FPGA/CPLD设计(高级篇)[M].北京：人民邮电出版社,2005.
[12]Altera Corporation. Introduction to QuartusⅡ Manual[EB], Apr 2005.
[13]于宗光,魏敬和,王国章.SOC和FPGA技术未来的发展趋势[J].电子与封装,2006,3(6)：3-4.
[14]周立功等.SOPC嵌入式系统基础教程[M].北京：北京航空航天大学出版社,2006.11.
[15]李秀娟,刘宪伟.基于Nios Ⅱ的SOPC系统开发与应用[J].电子技术,2007(3)：57-58.
[16]Nios Ⅱ Processor Reference Handbook. Altera Corporation[EB],2003.
[17]Nios Ⅱ Hardware Development Tutorial. Altera Corporation[EB],2005.
[18]Nios Ⅱ Software Developer's Handbook. AItera Corporation[EB],2005.
[19]Altrea Corp. Avalon Bus Specification Reference Manual[EB],2004.
[20]李明.基于SOPC的网络视频监控系统的设计与实现[D].大连：大连理工大学,2006.
[21]黄智伟,王彦,陈琼,潘礼,黄松.FPGA系统设计与实践[M].北京：电子工业出版杜,2005.
[22]蔡伟纲.Nios Ⅱ软件架构解析[M].西安：西安电子科技大学出版社,2007.
[23]裴建茹,李伟.基于Nios Ⅱ的嵌入式网络视频监控系统设计[J].视频应用与工程,2008,(2)：91-92.
[24]孙德印.基于彩色CMOS图像传感器的彩电白场光色检测系统[D].杭州：浙江大学光电工程学院,2003.
[25]OmniVision, OV7660 Single Chip CMOS VGA Color Digital Camera OmniVision Technologies[EB], Inc,2005.
[26]王建校,危建国.SOPC设计基础与实践[M].西安：西安电子科技大学出版社,2006.
[27]Altera Corporation. Cyclone FPGA Family Data Sheet[EB], March 2003.
[28]Altera. Cyclone Ⅱ FPGA Family[EB],2003.
[29]周立功等.SOPC嵌入式系统实验教程[M].北京：北京航空航天大学出版社,2006.11.
[30]池水明.FPGA在实时图像预处理中的应用[J].山两电子技术,2007,5,17-18.
[31]OmniVision Technologies Seril Camera Control Bus(SCCB) Specification[EB],2002.3.
[32]Whut_wj. OV7620/OV6620图像采集之深入探讨[EB],2006.4.
[33]吕鹏.基于FPGA的数字视频侦察监控系统设计[D].南京：南京理工大学,2009.
[34]于海,樊晓桠.基于FPGA异步FIFO的研究与实现[J].微电子学与计算机,2007,24(3)：210-216.
[35]赵效民.高手进阶,终极内存技术指南——完整／进阶版[J].电脑高手,2002,12.
[36]吴厚航.深入浅出玩转FPGA[M].北京：北京航空航天大学出版社,2010.
[37]Avalon Memory Mapped Interface Specification. Altera Corporation[EB]. Nov 2006.
[38]张瑞娟.基于视频图像的运动目标检测与跟踪算法研究[D].大连：大连理工大学,2008.
[39]王勇.基于统计方法的运动目标检测与跟踪技术研究[D].湖北：华中科技大学,2009.
[40]HOU Z, HAN C. A background reconstruction algorithm based on pixel intensity Classification[J]. Journal of Software,2005,16(9):1568-1576 (in Chinese)
[41]于成忠,朱骏,袁晓辉.基于背景差法的运动目标检测[J].东南大学学报,2005,(11)：160-161.