基于DSP的嵌入式数字仪表识别系统
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摘要
本文的研究是利用图像处理技术,实现数字仪表的自动识别。当今,数字仪表广泛地应用于各种场合。其可分为两类,一类是数显式数字仪表,另一类是机械式的数字仪表;由于数显式数字仪表大多功能比较齐全,对此类仪表的自动识别意义不大。而对于机械式的数字仪表,由于其使用量大,设备简单,价格低廉,计量单位和制造商在出厂校表时通常采用人眼或者光电采样的方法,但这两个方法效率比较低下,因此本文就是针对机械式数字仪表的自动识别系统进行开发。
目前,数字图像处理系统基本是通过图像采集卡进行视频采集,但是这种基于PC机的数字视频监控系统存在着一些缺点;如系统稳定性较差、成本高、不能在恶劣环境下使用等等。与此同时,科技的进步使得超大规模集成电路和嵌入式软硬件技术得到迅猛发展;诸如TI公司的数字信号处理(DSP)系统,Motorola公司的Powerpc等这些功能强大的嵌入式处理器价格越来越低,功能却越来越强大;尤其是DSP芯片,它丰富的外设接口和高度的可编程性使得图像处理的硬件和软件都更容易实现;为此将这种嵌入式处理器应用到图像处理系统中还克服了上述基于PC机系统的诸多缺点。正是由于越来越高的性价比加上体积小、成本低等独特优势使得嵌入式芯片在图像处理领域逐渐占有了一席之地。
本系统采用了TI公司推出的专用多媒体处理芯片TMS320DM642,实现对多仪表数字字符的识别,该系统可以实时采集4路视频的功能,有效降低了成本。采集到的数据经过处理后可通过EDMA进行本地存储。在该论文中,首先进行系统方案设计,然后是系统硬件的设计,其包括电源、监控电路、时钟电路和键盘等几部分;接下来进行系统软件设计,主要是系统引导方式、存储器空间分配、DM642初始化、以及通过RS-232接口与DSP连接的单片机(89C51)程序设计和BP神经网络识别数字字符算法等几个方面;最后讨论了系统的实际运行与结果分析,并展示了整个系统实物。
This paper is the use of image processing technology to realize the numeral instrumentation automatic recognition. Nowadays, the numeral instrument is widely used in many fields. There are two kinds of numeral instrument, the one is digital numeral instrument and the other is mechanic numeral instrument. Because the function of digital numeral instrument is usual comparatively stronger, auto recognition of this instrument is scarcely any meanings. But for mechanic numeral instrument, which is widely used, simple in manufacture and cheap in price, the adjustment of this instrument in measurement department and factory commonly uses the methods of human eyes or optic-to-electron sampler. The efficiency of these two methods is usually low. Consequently, this paper is aimed at the mechanical numeral instrument for the development of automatic identification system.
At present, most of digital image processing systems work by an image capturing card in PCI socket which work unstably. At the same time , the price is high and it can't work in bad circumstance and so on. On the other hand, because of quickly development of GSI and technology of embedded software and hardware, many powerful embedded processors, such as TI's DSP and Motorola's PowerPC, whose performance is higher and higher . But the price is lower and lower. Especially, a DSP chip includes abundance of peripheral interface and has very high programmed ability, which make the hardware and software of image processing system be implemented easily. But also, this embedded system conquers many deficiencies of the system based on PC. As a result of the increasing performance-price-ratio, adding in small area, low price and power consumption, embedded chips in the field of image processing occupies a place gradually.
In this system, the multimedia processing chip TMS320DM642 which is made by TI corporation is applied to implement the multi-instrument numeral character recognition. This system can capture 4-route video signals at the same time, which cuts down the cost effectively. The captured data are processed and stored into local stored RAM. Firstly in this paper, the system is projected. Secondly, the hardware of system is designed, including power and monitor circuit, clock circuit and keyboard circuit ect. Thirdly, the software of system is programed, including boot-loader of system, distribution of RAM, initialization of DM642 , microcontroller(89C51) programming code , BP neural network arithmetic and so on. Lastly, this paper discusses the practice result and the prototype model is exhibited .
目前,数字图像处理系统基本是通过图像采集卡进行视频采集,但是这种基于PC机的数字视频监控系统存在着一些缺点;如系统稳定性较差、成本高、不能在恶劣环境下使用等等。与此同时,科技的进步使得超大规模集成电路和嵌入式软硬件技术得到迅猛发展;诸如TI公司的数字信号处理(DSP)系统,Motorola公司的Powerpc等这些功能强大的嵌入式处理器价格越来越低,功能却越来越强大;尤其是DSP芯片,它丰富的外设接口和高度的可编程性使得图像处理的硬件和软件都更容易实现;为此将这种嵌入式处理器应用到图像处理系统中还克服了上述基于PC机系统的诸多缺点。正是由于越来越高的性价比加上体积小、成本低等独特优势使得嵌入式芯片在图像处理领域逐渐占有了一席之地。
本系统采用了TI公司推出的专用多媒体处理芯片TMS320DM642,实现对多仪表数字字符的识别,该系统可以实时采集4路视频的功能,有效降低了成本。采集到的数据经过处理后可通过EDMA进行本地存储。在该论文中,首先进行系统方案设计,然后是系统硬件的设计,其包括电源、监控电路、时钟电路和键盘等几部分;接下来进行系统软件设计,主要是系统引导方式、存储器空间分配、DM642初始化、以及通过RS-232接口与DSP连接的单片机(89C51)程序设计和BP神经网络识别数字字符算法等几个方面;最后讨论了系统的实际运行与结果分析,并展示了整个系统实物。
This paper is the use of image processing technology to realize the numeral instrumentation automatic recognition. Nowadays, the numeral instrument is widely used in many fields. There are two kinds of numeral instrument, the one is digital numeral instrument and the other is mechanic numeral instrument. Because the function of digital numeral instrument is usual comparatively stronger, auto recognition of this instrument is scarcely any meanings. But for mechanic numeral instrument, which is widely used, simple in manufacture and cheap in price, the adjustment of this instrument in measurement department and factory commonly uses the methods of human eyes or optic-to-electron sampler. The efficiency of these two methods is usually low. Consequently, this paper is aimed at the mechanical numeral instrument for the development of automatic identification system.
At present, most of digital image processing systems work by an image capturing card in PCI socket which work unstably. At the same time , the price is high and it can't work in bad circumstance and so on. On the other hand, because of quickly development of GSI and technology of embedded software and hardware, many powerful embedded processors, such as TI's DSP and Motorola's PowerPC, whose performance is higher and higher . But the price is lower and lower. Especially, a DSP chip includes abundance of peripheral interface and has very high programmed ability, which make the hardware and software of image processing system be implemented easily. But also, this embedded system conquers many deficiencies of the system based on PC. As a result of the increasing performance-price-ratio, adding in small area, low price and power consumption, embedded chips in the field of image processing occupies a place gradually.
In this system, the multimedia processing chip TMS320DM642 which is made by TI corporation is applied to implement the multi-instrument numeral character recognition. This system can capture 4-route video signals at the same time, which cuts down the cost effectively. The captured data are processed and stored into local stored RAM. Firstly in this paper, the system is projected. Secondly, the hardware of system is designed, including power and monitor circuit, clock circuit and keyboard circuit ect. Thirdly, the software of system is programed, including boot-loader of system, distribution of RAM, initialization of DM642 , microcontroller(89C51) programming code , BP neural network arithmetic and so on. Lastly, this paper discusses the practice result and the prototype model is exhibited .
引文
[1]李方慧,王飞,何佩混,TMS320C6000系列DSPs原理与应用[M],第二版,电子工业出版社,2003,1-2
[2]朱希志,罗良进,纵谈DSP的发展及应用[J],电脑知识与技术,第34期,2004,65-66
[3]TMS320DM642 Video/Imaging Fixed-Point Digital Signal Processor Data Manual,Texas Instruments Incorporated,SPRS200E,March 2004
[4]张国华,梁中华,一种基于模板匹配的人民币纸币面额识别方法[J],沈阳工业大学学报,第27卷第4期,2005.8,440-441
[5]叶晨洲,杨杰,宣国荣,车辆牌照字符识别[J],上海交通大学学报,第5卷第34期,2000,672-675
[6]郁梅,郁伯康,基于视觉的车辆牌照检测[J],计算机应用研究,1999.5,65-67
[7]袁曾任,人工神经元网络及其应用[M].北京:清华大学出版社,1999,35-40
[8]任绍彬,低电压DSP电源系统设计[J],电子工业专用设备,第137期,2005,58-59
[9]TPS54310-q1,Texas Instruments Incorporated,April 2005,9-10
[10]孙光,赵志敏,DSP复位问题研究[J],自动化与仪表,第6期,2006,71-72
[11]TPS3307-33-ep,Texas Instruments,December 2002,1-2
[12]TMS320C6201 System Clock Circuit Example[Z],SPRA430,Texas Instruments Incorporated,September 2001,9-10
[13]TMS320C6000 Peripherals Reference Guide[Z],spru190,Texas Instruments Incorpprated,February 2001,577-582
[14]TMS320C6000 DSP Designing for JTAG Emulation Reference Guide.pdf[Z],Texas Instruments Incorpprated,July 2003,1-10
[15]TMS320C6000DSP External Memory Interface(EMIF)Reference Guide,Texas Instruments Incorpprated,April 2004
[16]Hynix Co.,HY57V283220 Datasheet.pdf[Z],July 2004,2-3
[17]刘伟,刘洋,焦淑红,DSP片外高速海量SDRAM存储系统设计[J],单片机与 嵌入式系统应用,第1期,2006,32-33
[18]Spansion Co.,Am29LV640MT Datasheet.pdf[Z],July 2003,3-5
[19]何正军,朱善安,TMS320DM642 DSP二级引导程序的设计与实现[J],电子器件,第1卷第29期,2000,261-262
[20]TMS320C6000 DSP Inter-Integrated Circuit(I~2C)Module Reference Guide.Texas Instruments Incorpprated,October 2002,7-14
[21]杨恒,王召巴,高速模数转换器与TMS320C6000 DSP接口的FIFO实现[J],科技情报开发与经济,第16卷第16期,2006,229-230
[22]TVP515OPBS Ultralow-Power NTSC/PAL Video Decoder,Texas Instruments Incorpprated,May 2006.8-13
[23]TVPS150A Frequently Asked Questions-FAQs,Texas Instruments Incorpprated,May 2006,10-14
[24]Philips Semiconductors,SAAT105 Datasheet,October 2003,3-6
[25]郝勇庆,TMS320C6000DSP自动引导的方法和编程实现[J],火控雷达技术,第32期,2004.12,58-60
[26]TMS320DM642 Hardware Designer's Resource Guide,SPRAA51,Texas Instruments Incorpprated,July 2004,6-10
[27]Philips Semiconductors,THE I~2C-BUS SPECIFICATION.pdf[Z],VERSION 2.1,January 2000,8-14
[28]TMS320C64x DSP Video Port/VCXO Interpolated Control(VIC)Port Reference Guide,SPRU629,Texas Instruments Incorpprated,April 2000,34-146
[29]唐轶峻,申小阳,朱雯兰,隋成华.基于BP神经网络的数显仪表动态字符识别系统[J].光学仪器,2005,(06)
[30]阳明晔,张志勇,基于TMS320C6000系列DSP的C代码优化方法研究[J],微处理机,第2期,2004.4,59-61
[31]CASTLEMAN K R.Digital image processing[M].北京:清华大学出版社,1998.
[32]王建平,秦枫.灰度文本图像自适应二值化滤波算法设计及应用[J].合肥工业大学学报:自然科学版,2004,27(5):509-512.
[33]CASTLEMAN K R,WOODS R E.Digital image processing(second edition)[M].New Jersey:Prentice-hall International,Inc,2002:423-446.
[34]刘奕,蒋治华,一种利用颜色信息的车牌字符分割新算法[Z],计算机应用与软件,第08期,2005,98-100
[35]F.Martin Rodriguez,et al.New advances in Automatic Reading of VLP's.Proc.SPC-2000(IASTED),Marbella.Spain,2000.126-131.
[36]Arica N,Yarman-Vural F T.An overview of character recognition focused on off-line handwriting[J].Applications and Reviews.2001,31(2):216-233.
[37]K.Homik,Approximation Capabilities of Multilayer Feedforward Network.Neural Networks[J].1997,4(2):251-257.
[2]朱希志,罗良进,纵谈DSP的发展及应用[J],电脑知识与技术,第34期,2004,65-66
[3]TMS320DM642 Video/Imaging Fixed-Point Digital Signal Processor Data Manual,Texas Instruments Incorporated,SPRS200E,March 2004
[4]张国华,梁中华,一种基于模板匹配的人民币纸币面额识别方法[J],沈阳工业大学学报,第27卷第4期,2005.8,440-441
[5]叶晨洲,杨杰,宣国荣,车辆牌照字符识别[J],上海交通大学学报,第5卷第34期,2000,672-675
[6]郁梅,郁伯康,基于视觉的车辆牌照检测[J],计算机应用研究,1999.5,65-67
[7]袁曾任,人工神经元网络及其应用[M].北京:清华大学出版社,1999,35-40
[8]任绍彬,低电压DSP电源系统设计[J],电子工业专用设备,第137期,2005,58-59
[9]TPS54310-q1,Texas Instruments Incorporated,April 2005,9-10
[10]孙光,赵志敏,DSP复位问题研究[J],自动化与仪表,第6期,2006,71-72
[11]TPS3307-33-ep,Texas Instruments,December 2002,1-2
[12]TMS320C6201 System Clock Circuit Example[Z],SPRA430,Texas Instruments Incorporated,September 2001,9-10
[13]TMS320C6000 Peripherals Reference Guide[Z],spru190,Texas Instruments Incorpprated,February 2001,577-582
[14]TMS320C6000 DSP Designing for JTAG Emulation Reference Guide.pdf[Z],Texas Instruments Incorpprated,July 2003,1-10
[15]TMS320C6000DSP External Memory Interface(EMIF)Reference Guide,Texas Instruments Incorpprated,April 2004
[16]Hynix Co.,HY57V283220 Datasheet.pdf[Z],July 2004,2-3
[17]刘伟,刘洋,焦淑红,DSP片外高速海量SDRAM存储系统设计[J],单片机与 嵌入式系统应用,第1期,2006,32-33
[18]Spansion Co.,Am29LV640MT Datasheet.pdf[Z],July 2003,3-5
[19]何正军,朱善安,TMS320DM642 DSP二级引导程序的设计与实现[J],电子器件,第1卷第29期,2000,261-262
[20]TMS320C6000 DSP Inter-Integrated Circuit(I~2C)Module Reference Guide.Texas Instruments Incorpprated,October 2002,7-14
[21]杨恒,王召巴,高速模数转换器与TMS320C6000 DSP接口的FIFO实现[J],科技情报开发与经济,第16卷第16期,2006,229-230
[22]TVP515OPBS Ultralow-Power NTSC/PAL Video Decoder,Texas Instruments Incorpprated,May 2006.8-13
[23]TVPS150A Frequently Asked Questions-FAQs,Texas Instruments Incorpprated,May 2006,10-14
[24]Philips Semiconductors,SAAT105 Datasheet,October 2003,3-6
[25]郝勇庆,TMS320C6000DSP自动引导的方法和编程实现[J],火控雷达技术,第32期,2004.12,58-60
[26]TMS320DM642 Hardware Designer's Resource Guide,SPRAA51,Texas Instruments Incorpprated,July 2004,6-10
[27]Philips Semiconductors,THE I~2C-BUS SPECIFICATION.pdf[Z],VERSION 2.1,January 2000,8-14
[28]TMS320C64x DSP Video Port/VCXO Interpolated Control(VIC)Port Reference Guide,SPRU629,Texas Instruments Incorpprated,April 2000,34-146
[29]唐轶峻,申小阳,朱雯兰,隋成华.基于BP神经网络的数显仪表动态字符识别系统[J].光学仪器,2005,(06)
[30]阳明晔,张志勇,基于TMS320C6000系列DSP的C代码优化方法研究[J],微处理机,第2期,2004.4,59-61
[31]CASTLEMAN K R.Digital image processing[M].北京:清华大学出版社,1998.
[32]王建平,秦枫.灰度文本图像自适应二值化滤波算法设计及应用[J].合肥工业大学学报:自然科学版,2004,27(5):509-512.
[33]CASTLEMAN K R,WOODS R E.Digital image processing(second edition)[M].New Jersey:Prentice-hall International,Inc,2002:423-446.
[34]刘奕,蒋治华,一种利用颜色信息的车牌字符分割新算法[Z],计算机应用与软件,第08期,2005,98-100
[35]F.Martin Rodriguez,et al.New advances in Automatic Reading of VLP's.Proc.SPC-2000(IASTED),Marbella.Spain,2000.126-131.
[36]Arica N,Yarman-Vural F T.An overview of character recognition focused on off-line handwriting[J].Applications and Reviews.2001,31(2):216-233.
[37]K.Homik,Approximation Capabilities of Multilayer Feedforward Network.Neural Networks[J].1997,4(2):251-257.