铁路区间通过信号机编号识别系统的研究与实现
|
摘要
铁路区间通过信号机编号是保证铁路行车安全的重要标识,也是定期检测中必检项目内容。研究并实现铁路区间通过信号机编号识别系统,可以极大的减轻测试工作强度,也为测试提供更完整、更可靠、更全面的数据。
铁路区间通过信号机编号识别综合了图像处理和模式识别技术。论文研究了图像拍摄、图像预处理、铁路区间通过信号机柱的定位与分割、编号区域的定位与分割、编号的分割和编号识别等关键技术。在铁路区间通过信号机柱的定位、分割模块中采用了Hough快速检测边缘处理后的二值图像中的柱状物体,利用先验知识和投影直方图切割出区间通过信号机柱,并在分割出来的信号机柱图像中定位并分割出编号区域。在编号识别模块采用了模式识别中最基本的模板匹配算法,实验证明,该方法对信号机的编号识别是很有效的。
本系统在现有的电务试验车厢外面安装高速照相设备,到指定距离后,触动照相设备,将拍摄的铁路区间通过信号机的图像传入识别系统进行识别。论文对铁路区间通过信号机编号识别系统中的关键技术进行了研究、提出了有效的解决策略,并给出了实例。
论文提到的步骤和算法均己在软件平台上正确实现,以在电务试验车上采集的图像作为测试数据源进行测试,编号识别率达90%,满足了应用的基本要求。
Railway section signal serial number is an important ID of assuring railway traffic safety, as well as the project content detected indispensably during periodical detecting. The research and implement of a recognition system of railway section signal serial number will lighten a world of intension of the test work , also provide us more correctness and completeness and comprehensive data.
Both image processing and pattern recognition are adopted in the recognition of railway section signal serial number.The paper investigates some key techniques as follows: image shoot,image pretreatment,the localization and division of railway section overpassed signal post, the localization and division of serial number section,the division and recognition of serial number,etc. In the localization and segmentation module of the railway section signal post, Hough transform is used to detect quickly the pillarlike objects in the binary image after edge-handling, and transcendent knowledge and the projection histogram are used to get signal post image from which serial number districts are localized and divided. The most basically template matching algorithm of pattern recognition is adopted in the module of serial number recognition in the thesis, the experiments show that the method above-mentioned is very effective to the serial number recognition of signal.
In the system, outside the existing railway S &C test vehicle is equipped with high-speed cameras, when trains arrive for an appointed distance from it, the cameras is triggered to screen the signal, and the image is input into system for recognition. The paper researched and gave an effective solution to the key techniques of recognition system of railway section signal serial number, and instances are given.
Approaches and algorithms mentioned in the paper are all realized correctly in a software development platform, the experimental results used images gathered from the railway S &C test vehicle indicate the method achieves excellent performance in terms of recognition rates which is 90%,and it has met with the basical demand.
铁路区间通过信号机编号识别综合了图像处理和模式识别技术。论文研究了图像拍摄、图像预处理、铁路区间通过信号机柱的定位与分割、编号区域的定位与分割、编号的分割和编号识别等关键技术。在铁路区间通过信号机柱的定位、分割模块中采用了Hough快速检测边缘处理后的二值图像中的柱状物体,利用先验知识和投影直方图切割出区间通过信号机柱,并在分割出来的信号机柱图像中定位并分割出编号区域。在编号识别模块采用了模式识别中最基本的模板匹配算法,实验证明,该方法对信号机的编号识别是很有效的。
本系统在现有的电务试验车厢外面安装高速照相设备,到指定距离后,触动照相设备,将拍摄的铁路区间通过信号机的图像传入识别系统进行识别。论文对铁路区间通过信号机编号识别系统中的关键技术进行了研究、提出了有效的解决策略,并给出了实例。
论文提到的步骤和算法均己在软件平台上正确实现,以在电务试验车上采集的图像作为测试数据源进行测试,编号识别率达90%,满足了应用的基本要求。
Railway section signal serial number is an important ID of assuring railway traffic safety, as well as the project content detected indispensably during periodical detecting. The research and implement of a recognition system of railway section signal serial number will lighten a world of intension of the test work , also provide us more correctness and completeness and comprehensive data.
Both image processing and pattern recognition are adopted in the recognition of railway section signal serial number.The paper investigates some key techniques as follows: image shoot,image pretreatment,the localization and division of railway section overpassed signal post, the localization and division of serial number section,the division and recognition of serial number,etc. In the localization and segmentation module of the railway section signal post, Hough transform is used to detect quickly the pillarlike objects in the binary image after edge-handling, and transcendent knowledge and the projection histogram are used to get signal post image from which serial number districts are localized and divided. The most basically template matching algorithm of pattern recognition is adopted in the module of serial number recognition in the thesis, the experiments show that the method above-mentioned is very effective to the serial number recognition of signal.
In the system, outside the existing railway S &C test vehicle is equipped with high-speed cameras, when trains arrive for an appointed distance from it, the cameras is triggered to screen the signal, and the image is input into system for recognition. The paper researched and gave an effective solution to the key techniques of recognition system of railway section signal serial number, and instances are given.
Approaches and algorithms mentioned in the paper are all realized correctly in a software development platform, the experimental results used images gathered from the railway S &C test vehicle indicate the method achieves excellent performance in terms of recognition rates which is 90%,and it has met with the basical demand.
引文
[1]中华人民共和国铁道部计划司.铁计[2006]173号.铁路“十一五”规划.北京:中国铁道出版社,2006-9-8
[2]林路.铁道知识[J].中国铁道出版社,2007,(2):4-9
[3]周平.铁道概论[M].北京:中国铁道出版社,2006.135-140
[4]林瑜筠.铁路信号基础[M].北京:中国铁道出版社,2006.50-83
[5]中华人民共和国铁道部.铁令[2006]29号.铁路技术管理规程.北京:中国铁道出版社,2006-9-27
[6]中华人民共和国铁道部.铁运[2006]127号.铁路信号维护规范.北京:中国铁道出版社,2006-9.1
[7]赵会兵.虚拟仪器技术规范与系统集成[M].北京:清华大学出版社,2003.1-5
[8]AH Taner,NM White.Virtul Instrumentation,A Solution to the Design Complexitily in Intelligent Instruments[J].Measurement &Control.1996,(5):29
[9]余儿忠,罗金文,姜震.基于虚拟仪器的轨道交通测试自动化[J].华东交通大学学报,2005,22(1):36-39
[10]游柳,赵会兵.基于虚拟仪器技术的电务试验车自动测试系统[J].铁道通信信号,2006,42(7):14-15
[11]李睿,赵会兵.基于虚拟仪器技术的铁路信号嵌入式测试系统[J].铁道通信信号,2007,43(1):56-58
[12]Gary W.Johnson,Richard Jennings z著.武嘉澍,陆劲昆译.LabView图形编程[M].北京:北京大学出版社,2002,4-15
[13]曹刚.运动车辆识别技术研究:[博士学位论文].四川:四川大学,2004
[14]徐建闽,贺敬凯.车牌自动识别技术分析[J],交通与计算机,2002,20(2):7-12
[15]Parisi R,Claudio E D,Lucharelli G,Car Plate Recognition by Neural Networks and Image Processing[J],IEEE International System On Circuit and System 1998,3(6):1960-1980
[16]Hans A Hegt,Ron J De La Haye,Nadeem A Khan.A high performance license plate recognition system[J].Proceedings of IEEE International Conference on System,Man and Cybernetics,1998,(5):4357-4362
[17]Naito T,Tsukada T,Yamada,et al.Robust license-plate recognition method for passing vehicles under outside environment.IEEE Transactions on Vehicular Technology.2000,49(6):2309-2319
[18]李文岩.汽车牌照识别技术的研究:[硕士学位论文].陕西:西安电子科技大学,2006
[19]安勇,张高伟.基于灰度图像的车牌识别系统[J].计算机工程与科学,2006,28(2):65-66+69
[20]Jun Ohya,et al.,Recognizing character In scene images.IEEE fans.On Pattern Analysis And Machine Intelligence,1994,16(2):214-220
[21]李树广,刘允才.智能交通的发展与研究[J].微型电脑应用,2005,21(6):1-6
[22]李开成,毛俊杰,傅世善.国外铁路通信信号新技术纵览[M].北京:中国铁道出版社,2005.22-62
[23]Yang C K,TsaiW H.Reduction of color space dimensionality by moment p reserving thresholding and its application for edge detection in color images[J].Pattern Recognition Letters,1996,17(5):481-490.
[24]周金和,彭福堂.一种有选择的图像灰度化方法[J].计算机工程,2006,32(20):198-200
[25]Stark J A.Adaptive image contrast enhancement using generalizations of histogram equalization.IEEE Trans On Image Processing,2000,9(5):889-896
[26]蔡曙山.论数字化[J].中国社会科学,2001,(4)33-42+203-204
[27]Kang M G,Katsaggelos A K.General choice of the regularization functional in regularization image restoration.IEEE Trans on Image Processing.1995,4(5):594-602
[28]黄伟,龚沛曾.图像压缩中的几种编码方法[J].计算机应用研究,2003,20(8):67-69+72
[29]Pavlidis T and Liow Y T.Integrating Region Growing and Edge Detection.IEEE Trans.Pattern Analysis and Machine Intelligence.1990,12(3):225-233
[30]章毓晋.图象分割[M].北京:科学出版社,2000.200-350
[31]肖志涛,国澄明,侯正信.图像特征检测算法的分析与研究[J].中国图象图形学报,2004,9(12):20-26
[32]Vanderbrug G J,et al.Two-stage template matching.IEEE Trans.on Compute.1977,C-26(4):384-393
[33]陈跃.图像分析系统及其在生物医学中的应用[J].生物医学工程学杂志,2003,20(1):171-174
[34]Ming Tu Te,Chen Chin Hsing.A fast Two Stage Classification Method for High-Dimensional Remote Sensing Data.IEEE Trans.on Geoscience and Remote Sensing.1998,36(1):182-191
[35]诸葛斌,冯焕清,周荷琴.基于PC机的医学图像三维表面重建[J].航天医学与医学工程,2002,15(4):296-299
[36]黄祥林,沈兰荪.基于内容的图像检索技术研究[J].电子学报,2002,30(7):130-136
[37]易开祥,孙鑫.数字水印技术研究进展[J].中国图象图形学报,2001,6(2):11-17
[38]陈景航,杨宜民,陈浩杰.新型足球机器人视觉系统的研究[J].计算机应用,2005,25(8):221-223
[39]Sato I,Sato Y,Ikeucki K.Acquiring a radiance distribution to superimpose virtual objects onto a real scene.IEEE Transactions on Visualization and Computer Graphics.1999,5(1):1-12
[40]周前祥,姜世忠,姜国华.虚拟现实技术的研究现状与进展[J].计算机仿真,2003,20(7):3-6
[41]郑建利.移频自动站间闭塞联系电路设计[J].铁道通信信号,2001,38(8):18-20
[42]Wallace G K.The JPEG Still Picture Compression Standard[J].IEEE Trans.CousumerElectrouics,1992,38(1):10-60
[43]Christopoulos C,Skodras A,Ebrahimi T.The JPEG2000 Still Image Coding System,An Overview[J].IEEE Trans.on Consumer Electronics 2000,46(4):1103-1127
[44]Michael W,Marcellin A.An overview of JPEG-2000[A].Proc.IEEE Data Compression Conference[C],2000:100-541
[45]陈传波.数字图像处理[M].北京:机械工业出版社,2004.150-300
[46]高守传,姚领田.Visual C++实践与提高.数字图像处理与工程应用篇[M].北京:铁道出版社,2006:51-89
[47]李刚,黎燕,樊晓平.基于动态数学形态运算的二值图像边界提取[J].计算机工程与应用,2005,41(24):72-74
[48]王树文,闫成新,张天序.数学形态学在图像处理中的应用[J].计算机工程与应用,2004,40(32):89-92
[49]徐建华.图象处理与分析[M].北京:科学出版社,1992.194-195
[50]Ballard D H.Ceneralizing the hough transform to detect arbitrary shapes[J], Pattem Recognition,1981,13(4):111-122
[51]龙钧宇,金连文.一种基于全局均值和局部方差的图像二值化方法[J].计算机工程,2004,30(2):70-72
[52]Casey,R.C;Lecolinet,E.A survey of methods and strategies in character segmentation.Pattern Analysis and Machine Intelligence,1996,7(18):690-706
[53]边肇祺,张学工.模式识别[M].北京:清华大学出版社,2000:2-20
[54]肖健华.智能模式识别方法[M].广州:华南理工大学出版社,2006:2-20
[55]罗中兵,付忠良,阮波.一种改进的模板匹配算法[J].计算机应用,2002,22(3):30-32
[56]Guyon,H.Application of neural networks to character recognition[J],International Journal of Pattern Recognition and Artificial Intelligence,1991,5(3):353-382
[57]张宏烈.支持向量机在字符识别中的应用研究[J].微型计算机信息,2006,(04Z):245-247
[58]VAPNIK V N.The nature of statistical learning theory[M].New York:Springer Verlag,1995.
[59]陈宁江,李介谷.用归一化灰度组合法进行图像匹配[J].红外与激光工程,2000,29(5):8-21
[60]袁源,李炳法,杨杰.基于频域双线性插值的数字水印算法[J].计算机应用,2004,24(1):87-89
[61]杨淑莹.图像模式识别VC++技术实现[M].北京:清华大学出版社,2005:25-45
[2]林路.铁道知识[J].中国铁道出版社,2007,(2):4-9
[3]周平.铁道概论[M].北京:中国铁道出版社,2006.135-140
[4]林瑜筠.铁路信号基础[M].北京:中国铁道出版社,2006.50-83
[5]中华人民共和国铁道部.铁令[2006]29号.铁路技术管理规程.北京:中国铁道出版社,2006-9-27
[6]中华人民共和国铁道部.铁运[2006]127号.铁路信号维护规范.北京:中国铁道出版社,2006-9.1
[7]赵会兵.虚拟仪器技术规范与系统集成[M].北京:清华大学出版社,2003.1-5
[8]AH Taner,NM White.Virtul Instrumentation,A Solution to the Design Complexitily in Intelligent Instruments[J].Measurement &Control.1996,(5):29
[9]余儿忠,罗金文,姜震.基于虚拟仪器的轨道交通测试自动化[J].华东交通大学学报,2005,22(1):36-39
[10]游柳,赵会兵.基于虚拟仪器技术的电务试验车自动测试系统[J].铁道通信信号,2006,42(7):14-15
[11]李睿,赵会兵.基于虚拟仪器技术的铁路信号嵌入式测试系统[J].铁道通信信号,2007,43(1):56-58
[12]Gary W.Johnson,Richard Jennings z著.武嘉澍,陆劲昆译.LabView图形编程[M].北京:北京大学出版社,2002,4-15
[13]曹刚.运动车辆识别技术研究:[博士学位论文].四川:四川大学,2004
[14]徐建闽,贺敬凯.车牌自动识别技术分析[J],交通与计算机,2002,20(2):7-12
[15]Parisi R,Claudio E D,Lucharelli G,Car Plate Recognition by Neural Networks and Image Processing[J],IEEE International System On Circuit and System 1998,3(6):1960-1980
[16]Hans A Hegt,Ron J De La Haye,Nadeem A Khan.A high performance license plate recognition system[J].Proceedings of IEEE International Conference on System,Man and Cybernetics,1998,(5):4357-4362
[17]Naito T,Tsukada T,Yamada,et al.Robust license-plate recognition method for passing vehicles under outside environment.IEEE Transactions on Vehicular Technology.2000,49(6):2309-2319
[18]李文岩.汽车牌照识别技术的研究:[硕士学位论文].陕西:西安电子科技大学,2006
[19]安勇,张高伟.基于灰度图像的车牌识别系统[J].计算机工程与科学,2006,28(2):65-66+69
[20]Jun Ohya,et al.,Recognizing character In scene images.IEEE fans.On Pattern Analysis And Machine Intelligence,1994,16(2):214-220
[21]李树广,刘允才.智能交通的发展与研究[J].微型电脑应用,2005,21(6):1-6
[22]李开成,毛俊杰,傅世善.国外铁路通信信号新技术纵览[M].北京:中国铁道出版社,2005.22-62
[23]Yang C K,TsaiW H.Reduction of color space dimensionality by moment p reserving thresholding and its application for edge detection in color images[J].Pattern Recognition Letters,1996,17(5):481-490.
[24]周金和,彭福堂.一种有选择的图像灰度化方法[J].计算机工程,2006,32(20):198-200
[25]Stark J A.Adaptive image contrast enhancement using generalizations of histogram equalization.IEEE Trans On Image Processing,2000,9(5):889-896
[26]蔡曙山.论数字化[J].中国社会科学,2001,(4)33-42+203-204
[27]Kang M G,Katsaggelos A K.General choice of the regularization functional in regularization image restoration.IEEE Trans on Image Processing.1995,4(5):594-602
[28]黄伟,龚沛曾.图像压缩中的几种编码方法[J].计算机应用研究,2003,20(8):67-69+72
[29]Pavlidis T and Liow Y T.Integrating Region Growing and Edge Detection.IEEE Trans.Pattern Analysis and Machine Intelligence.1990,12(3):225-233
[30]章毓晋.图象分割[M].北京:科学出版社,2000.200-350
[31]肖志涛,国澄明,侯正信.图像特征检测算法的分析与研究[J].中国图象图形学报,2004,9(12):20-26
[32]Vanderbrug G J,et al.Two-stage template matching.IEEE Trans.on Compute.1977,C-26(4):384-393
[33]陈跃.图像分析系统及其在生物医学中的应用[J].生物医学工程学杂志,2003,20(1):171-174
[34]Ming Tu Te,Chen Chin Hsing.A fast Two Stage Classification Method for High-Dimensional Remote Sensing Data.IEEE Trans.on Geoscience and Remote Sensing.1998,36(1):182-191
[35]诸葛斌,冯焕清,周荷琴.基于PC机的医学图像三维表面重建[J].航天医学与医学工程,2002,15(4):296-299
[36]黄祥林,沈兰荪.基于内容的图像检索技术研究[J].电子学报,2002,30(7):130-136
[37]易开祥,孙鑫.数字水印技术研究进展[J].中国图象图形学报,2001,6(2):11-17
[38]陈景航,杨宜民,陈浩杰.新型足球机器人视觉系统的研究[J].计算机应用,2005,25(8):221-223
[39]Sato I,Sato Y,Ikeucki K.Acquiring a radiance distribution to superimpose virtual objects onto a real scene.IEEE Transactions on Visualization and Computer Graphics.1999,5(1):1-12
[40]周前祥,姜世忠,姜国华.虚拟现实技术的研究现状与进展[J].计算机仿真,2003,20(7):3-6
[41]郑建利.移频自动站间闭塞联系电路设计[J].铁道通信信号,2001,38(8):18-20
[42]Wallace G K.The JPEG Still Picture Compression Standard[J].IEEE Trans.CousumerElectrouics,1992,38(1):10-60
[43]Christopoulos C,Skodras A,Ebrahimi T.The JPEG2000 Still Image Coding System,An Overview[J].IEEE Trans.on Consumer Electronics 2000,46(4):1103-1127
[44]Michael W,Marcellin A.An overview of JPEG-2000[A].Proc.IEEE Data Compression Conference[C],2000:100-541
[45]陈传波.数字图像处理[M].北京:机械工业出版社,2004.150-300
[46]高守传,姚领田.Visual C++实践与提高.数字图像处理与工程应用篇[M].北京:铁道出版社,2006:51-89
[47]李刚,黎燕,樊晓平.基于动态数学形态运算的二值图像边界提取[J].计算机工程与应用,2005,41(24):72-74
[48]王树文,闫成新,张天序.数学形态学在图像处理中的应用[J].计算机工程与应用,2004,40(32):89-92
[49]徐建华.图象处理与分析[M].北京:科学出版社,1992.194-195
[50]Ballard D H.Ceneralizing the hough transform to detect arbitrary shapes[J], Pattem Recognition,1981,13(4):111-122
[51]龙钧宇,金连文.一种基于全局均值和局部方差的图像二值化方法[J].计算机工程,2004,30(2):70-72
[52]Casey,R.C;Lecolinet,E.A survey of methods and strategies in character segmentation.Pattern Analysis and Machine Intelligence,1996,7(18):690-706
[53]边肇祺,张学工.模式识别[M].北京:清华大学出版社,2000:2-20
[54]肖健华.智能模式识别方法[M].广州:华南理工大学出版社,2006:2-20
[55]罗中兵,付忠良,阮波.一种改进的模板匹配算法[J].计算机应用,2002,22(3):30-32
[56]Guyon,H.Application of neural networks to character recognition[J],International Journal of Pattern Recognition and Artificial Intelligence,1991,5(3):353-382
[57]张宏烈.支持向量机在字符识别中的应用研究[J].微型计算机信息,2006,(04Z):245-247
[58]VAPNIK V N.The nature of statistical learning theory[M].New York:Springer Verlag,1995.
[59]陈宁江,李介谷.用归一化灰度组合法进行图像匹配[J].红外与激光工程,2000,29(5):8-21
[60]袁源,李炳法,杨杰.基于频域双线性插值的数字水印算法[J].计算机应用,2004,24(1):87-89
[61]杨淑莹.图像模式识别VC++技术实现[M].北京:清华大学出版社,2005:25-45