煤场车辆监控与识别系统的研究与开发
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摘要
随着经济的发展,煤炭的需求也在不断的提高,煤炭运输中运煤车辆的运输承担着主要作用,尤其是运煤码头,火电厂,某些大企业用煤量极大,运煤列车来往更是频繁。汽车运输调配煤炭一直是煤炭运销工作的重点。到目前为止,一些煤场中运煤车辆监控、称重、记录等工作,主要采用人工的方法管理。这种依赖人工方式的车辆管理模式,存在着许多弊端和安全隐患。煤场车辆监控与识别系统主要目的是在保证车辆通行的前提下,最大限度的减少煤炭的流失。在系统中加入车辆、司机的自动识别及车辆重量的自动称重。不仅可以减轻收费员的劳动强度,更能解决现有收费系统中存在的漏洞。
本论文详细讨论了一种可应用于煤场车辆监控与识别的方法。本文的贡献有：第一部分设计了系统的硬件,对车辆到达感应部分、重量检测电路、射频卡识别部分、监视与拍摄部分硬件进行选型。对硬件进行调试,使其能与上位机进行良好的通信。
第二部分为软件设计,基于Delphi 7.0软件平台进行开发,采用Access数据库完成对监控系统数据及多媒体信息的保存、查询、删除等功能。设计了软件工作界面,软件能够完成对煤场现场监控、车辆查询、图像识别、车辆称重、车辆身份识别等功能。该系统能实现良好的控制效果,提高煤场车辆监控的效率。
第三部分采用了一种结合车牌几何特征及颜色特征的车牌定位算法,首先对图像噪声进行处理,然后对车牌区域集合形状以及颜色、象素等分析。分析得到可能连通体,并对连通体进行组链。从多个组链中选出最大可能的链,从而定位出车牌区域。对于煤场大型车辆具有很好的针对性,取得很好的车牌定位效果。
通过实际硬件实验和对采集来的图片的实验,实验证明系统能够识别车辆的身份,重量等信息,实验结果表明,本文所提出针对煤场车辆监控与识别系统方法的有效和实用性。
With development of economic, the demand for coal has been increased. Vehicles play an important role in coal carrying. In particular, coal terminals, power plants, some big companies, coal vehicle comes and back more frequently.As far as now, vehicle transport is the focus of coal's transportation and sale.Many vehicle's weighting,recording and monitoring in coal field is mainly managed by artificial methods.There are so many drawbacks and security risk in artifical management model.Coal market vehicle monitoring and identification'aim is to ensure the premise of vehicles and to minimize the loss of coal.System can identify the driver and vehicle'identity. The system can measure the height of the vehicle automaticly. System can not only to reduce the intensity of charge, but also solve the loopholes in the system.
This paper discussed a method in detail.This method can be applied to coal market vehicle monitoring and identification system. The main contribution of this paper is:
In the first part, design the system'hardware.Selectding the hardware to vehicle arrival part, weighting detection circuit, radio frequency identification cards, monitoring and photoing part. Let them can communicate to computer very well.
The second part is the software's design. The design is based on the Delphi 7.0 platform. Access dtabase is use to save, inquery and delete the information of vehicle monitoring system. Dsign the interface of the software, the software can complete the function of vehicle monitoring, vehicle information, image recognition, wehicle weighting and vehicle identification. The system can reach good control effect and enhance good efficiency.
In the third part disscused the license plate location algorithm in detail. This algorithm is based on the character of license plate's shape and color character.Fistly, we fiter out the noise of vehicle plate license image. Then give analysis to the color and pixels region. After analysis, get the connecttiong component area. Give the Analysis to the connecting componet area and group special chains. Accroding to analysis the chain characteristics, select the most probably chains in several chains. At last positionting the regiong of licese plate. This method has an good effect to the license plate's location.
Though the experiment of actual and the collection picture.Experiment show the system can identify the identity of vehicles, weight and other information. The result of experiment show the coal maket vehicle monitoring and identification is effective and practical.
本论文详细讨论了一种可应用于煤场车辆监控与识别的方法。本文的贡献有：第一部分设计了系统的硬件,对车辆到达感应部分、重量检测电路、射频卡识别部分、监视与拍摄部分硬件进行选型。对硬件进行调试,使其能与上位机进行良好的通信。
第二部分为软件设计,基于Delphi 7.0软件平台进行开发,采用Access数据库完成对监控系统数据及多媒体信息的保存、查询、删除等功能。设计了软件工作界面,软件能够完成对煤场现场监控、车辆查询、图像识别、车辆称重、车辆身份识别等功能。该系统能实现良好的控制效果,提高煤场车辆监控的效率。
第三部分采用了一种结合车牌几何特征及颜色特征的车牌定位算法,首先对图像噪声进行处理,然后对车牌区域集合形状以及颜色、象素等分析。分析得到可能连通体,并对连通体进行组链。从多个组链中选出最大可能的链,从而定位出车牌区域。对于煤场大型车辆具有很好的针对性,取得很好的车牌定位效果。
通过实际硬件实验和对采集来的图片的实验,实验证明系统能够识别车辆的身份,重量等信息,实验结果表明,本文所提出针对煤场车辆监控与识别系统方法的有效和实用性。
With development of economic, the demand for coal has been increased. Vehicles play an important role in coal carrying. In particular, coal terminals, power plants, some big companies, coal vehicle comes and back more frequently.As far as now, vehicle transport is the focus of coal's transportation and sale.Many vehicle's weighting,recording and monitoring in coal field is mainly managed by artificial methods.There are so many drawbacks and security risk in artifical management model.Coal market vehicle monitoring and identification'aim is to ensure the premise of vehicles and to minimize the loss of coal.System can identify the driver and vehicle'identity. The system can measure the height of the vehicle automaticly. System can not only to reduce the intensity of charge, but also solve the loopholes in the system.
This paper discussed a method in detail.This method can be applied to coal market vehicle monitoring and identification system. The main contribution of this paper is:
In the first part, design the system'hardware.Selectding the hardware to vehicle arrival part, weighting detection circuit, radio frequency identification cards, monitoring and photoing part. Let them can communicate to computer very well.
The second part is the software's design. The design is based on the Delphi 7.0 platform. Access dtabase is use to save, inquery and delete the information of vehicle monitoring system. Dsign the interface of the software, the software can complete the function of vehicle monitoring, vehicle information, image recognition, wehicle weighting and vehicle identification. The system can reach good control effect and enhance good efficiency.
In the third part disscused the license plate location algorithm in detail. This algorithm is based on the character of license plate's shape and color character.Fistly, we fiter out the noise of vehicle plate license image. Then give analysis to the color and pixels region. After analysis, get the connecttiong component area. Give the Analysis to the connecting componet area and group special chains. Accroding to analysis the chain characteristics, select the most probably chains in several chains. At last positionting the regiong of licese plate. This method has an good effect to the license plate's location.
Though the experiment of actual and the collection picture.Experiment show the system can identify the identity of vehicles, weight and other information. The result of experiment show the coal maket vehicle monitoring and identification is effective and practical.
引文
1.潘锋.运煤车连接方式自动检测系统的研究[D],燕山大学,2003.
2.魏国庆.入场煤管理系统在煤炭运销中的应用[J],山东煤炭科技,2008,6(3)：1.
3.李亮.基于汽车电子牌照识别技术的车辆监控与防暴技术[D],北京工商大学,2006.
4.郑刚.车牌识别系统中相关技术的研究[D],东北大学,2007.
5.张晓峰.超声波车辆检测中的抗干扰技术[J],电子技术应用,1999,9(25)：37.
6. Haibing Huang. Vehicle License Plate Location Based on Harris Corner Detection [C], 2008, IEEE International Joint Conference on Neural Networks, Vols 1:352.
7. V. Koval.Smart. License Plate Recognition System Based on Image Processing Using Neural Network [C],2003,2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems, Sep 08-10:123.
8.崔家磊.风云一号接收系统定时同步与PCI接口研究[D],西安电子科技,2008.
9.韩呈.公路动态称重系统的研究[D],太原理工大学,2006.
10.马鹏阁.智能射频卡系统与车道控制系统的研究和实现[D],郑州大学,2004.
11.李智.基于FPGA和面阵CCD摄像头的动态光谱数据采集和预处理[D],天津大学,2007.
12.何艺桦.基于CCD的小型光谱分析仪器与化学发光新技术[D],四川大学,2007.
13.刘俊杰.新型DCS组态软件框架和数据库的研究与开发[D],2008.
14.孙波.基于Delphi的多层分布式数据库的设计及其在远程抄表系统中的应用[D],山东科技大学,2007.
15. Borland Corporation.Borland Delphi 6 Develops Guide[M].USA:Borland Corporation,135-152.
16.赵永杰.基于Delphi的排放测试系统主控计算机系统开发,长安大学,2006.
17.韩娜.基于ADO技术的软构件库的开发研究[D],西安电子科技,2006.
18. Bei Chen. An Efficient Algorithm on Vehicle License Plate Location, Northwestern Polytechnical University [C],2008, IEEE International Conference On Automation And Logistics, Vols 6:1386.
19.金小莉.汽车牌照自动定位算法研究,西安电子科技大学[D],2004
20. Charl Coetzee. PC Based Number Plate Recognition System [C], Proc.1998, IEEE International SymPosium on Industrial Electronics, Vols 1:605-610.
21. Kamat. An Efficient Implementation of the Hough Transform for Detecting Vehicle License Plates Using DSP'S [C].1995, Real-Time Technology and Applications Symposium, May 15-17:58-59.
22. J.Barroso. Number Plate Reading Using Computer Vision[C],1997, Proc.IEEE International SymPosium on Industrial Electronics, Vols 2:761-763.
23.杨家辉.基于综合特征的牌照定位与字符分割技术的研究,西南交通大学[D],2007.
24. Eun Ryung Lee. Automatic Recognition of a Car License Plate Using Color Image Processing [C], Proc.IEEE International SymPosium on Industrial Electronics,1994, Vols 3: 310-304.
25.周亮.基于神经网络的车牌识别算法研究[D],青岛科技大学,2007.
26. Raus. Michael. Reading Car License Plates By The Use Of Artificial Neural Networks.IEEE [C],1996,38th Midwest Symposium On Circuirs and Systems, Proceedings, Vols 1 and 2:538-541.
27. K.K.Kim. Learning-Based Approach for License Plate Recognition [C],2000, Neural Networks For Signal Processing, Vols 1 and 2:614-623.
28.姚金良.基于连通域的图像中场景文本定位[J],高技术通讯,2007,17(6)：612-617.
29.蒋人杰.基于学习的自然背景中文本提取[D],上海交通大学,2007.
30.路轶.复杂背景字符识别前处理研究[D],华南理工大学,2005.
31.有峥嵘.车轮踏面缺陷检测系统的研究[D],西南交通大学,2008.
32.王峰.复杂背景下的车牌定位及字符分割[D],西北工业大学,2007.
33.郭天舒.基于车牌自身结构特征的车牌定位算法[J],计算机与信息技术,2008,6(2)：51.
34.罗菁.基于车辆视觉导航的图像预处理的研究[D],武汉理工大学,2008.
35.蔡元学.图像分割与骨架线提取中的Snakes方法及其应用研究[D],天津大学,2007.
36.胡佩雯.基于视频的实时交通流检测系统的研究[D],武汉理工大学,2008.
2.魏国庆.入场煤管理系统在煤炭运销中的应用[J],山东煤炭科技,2008,6(3)：1.
3.李亮.基于汽车电子牌照识别技术的车辆监控与防暴技术[D],北京工商大学,2006.
4.郑刚.车牌识别系统中相关技术的研究[D],东北大学,2007.
5.张晓峰.超声波车辆检测中的抗干扰技术[J],电子技术应用,1999,9(25)：37.
6. Haibing Huang. Vehicle License Plate Location Based on Harris Corner Detection [C], 2008, IEEE International Joint Conference on Neural Networks, Vols 1:352.
7. V. Koval.Smart. License Plate Recognition System Based on Image Processing Using Neural Network [C],2003,2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems, Sep 08-10:123.
8.崔家磊.风云一号接收系统定时同步与PCI接口研究[D],西安电子科技,2008.
9.韩呈.公路动态称重系统的研究[D],太原理工大学,2006.
10.马鹏阁.智能射频卡系统与车道控制系统的研究和实现[D],郑州大学,2004.
11.李智.基于FPGA和面阵CCD摄像头的动态光谱数据采集和预处理[D],天津大学,2007.
12.何艺桦.基于CCD的小型光谱分析仪器与化学发光新技术[D],四川大学,2007.
13.刘俊杰.新型DCS组态软件框架和数据库的研究与开发[D],2008.
14.孙波.基于Delphi的多层分布式数据库的设计及其在远程抄表系统中的应用[D],山东科技大学,2007.
15. Borland Corporation.Borland Delphi 6 Develops Guide[M].USA:Borland Corporation,135-152.
16.赵永杰.基于Delphi的排放测试系统主控计算机系统开发,长安大学,2006.
17.韩娜.基于ADO技术的软构件库的开发研究[D],西安电子科技,2006.
18. Bei Chen. An Efficient Algorithm on Vehicle License Plate Location, Northwestern Polytechnical University [C],2008, IEEE International Conference On Automation And Logistics, Vols 6:1386.
19.金小莉.汽车牌照自动定位算法研究,西安电子科技大学[D],2004
20. Charl Coetzee. PC Based Number Plate Recognition System [C], Proc.1998, IEEE International SymPosium on Industrial Electronics, Vols 1:605-610.
21. Kamat. An Efficient Implementation of the Hough Transform for Detecting Vehicle License Plates Using DSP'S [C].1995, Real-Time Technology and Applications Symposium, May 15-17:58-59.
22. J.Barroso. Number Plate Reading Using Computer Vision[C],1997, Proc.IEEE International SymPosium on Industrial Electronics, Vols 2:761-763.
23.杨家辉.基于综合特征的牌照定位与字符分割技术的研究,西南交通大学[D],2007.
24. Eun Ryung Lee. Automatic Recognition of a Car License Plate Using Color Image Processing [C], Proc.IEEE International SymPosium on Industrial Electronics,1994, Vols 3: 310-304.
25.周亮.基于神经网络的车牌识别算法研究[D],青岛科技大学,2007.
26. Raus. Michael. Reading Car License Plates By The Use Of Artificial Neural Networks.IEEE [C],1996,38th Midwest Symposium On Circuirs and Systems, Proceedings, Vols 1 and 2:538-541.
27. K.K.Kim. Learning-Based Approach for License Plate Recognition [C],2000, Neural Networks For Signal Processing, Vols 1 and 2:614-623.
28.姚金良.基于连通域的图像中场景文本定位[J],高技术通讯,2007,17(6)：612-617.
29.蒋人杰.基于学习的自然背景中文本提取[D],上海交通大学,2007.
30.路轶.复杂背景字符识别前处理研究[D],华南理工大学,2005.
31.有峥嵘.车轮踏面缺陷检测系统的研究[D],西南交通大学,2008.
32.王峰.复杂背景下的车牌定位及字符分割[D],西北工业大学,2007.
33.郭天舒.基于车牌自身结构特征的车牌定位算法[J],计算机与信息技术,2008,6(2)：51.
34.罗菁.基于车辆视觉导航的图像预处理的研究[D],武汉理工大学,2008.
35.蔡元学.图像分割与骨架线提取中的Snakes方法及其应用研究[D],天津大学,2007.
36.胡佩雯.基于视频的实时交通流检测系统的研究[D],武汉理工大学,2008.