集装箱自动识别系统研究
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摘要
集装箱自动识别系统在海关物流监控系统、港务局集装箱管理系统、场站集装箱管理系统、加工区监管系统、运输行业集装箱管理系统等领域有着广泛的应用。基于光学字符识别技术的集装箱自动识别系统主要是通过图像处理技术，自动提取集装箱箱号并识别，由于其具有不需要在集装箱上增加任何其他设备以及可通过人机界面，加入人工干预提高系统性能的优点，发展较快，日益受到人们的重视。
本文研究的是基于光学字符识别技术的集装箱自动识别系统，简要介绍了系统的工作原理，分析了集装箱原始图像的特点，详细阐述了系统处理流程：图像预处理、箱号字符区域定位、箱号字符区域二值化及字符分割、识别预处理、特征提取和字符识别。本文运用形态学运算消除背景、进行灰度变换增强对比度和进行平滑过滤噪声来完成图像的预处理。对预处理后的图像进行边缘提取，先消除非字符边缘的长线条，再用形态学运算消除干扰边缘和噪声。针对字符排列相对集中的特点，详细介绍了如何利用边缘结合形态学定位箱号字符的方法来实现箱号字符的定位。选用合适的二值化方法完成字符区域的灰度图像到二值图像的转换。利用基于求连通区域与投影相结合的字符切分技术完成字符的分割。讨论了字符识别技术，实现了利用图像矩特征进行字符识别以及利用数字的结构特征识别数字。
实验表明，文中的箱号定位方法是有效的，字符识别方法亦具有一定的参考价值。
Container Automatic Equipment Identification (AEI) system can be widely applied to material circulation monitoring system in customs, to container management system in harbor bureau, container depot, and transportation industry, and to monitoring and management system in machining center, etc. Container AEI system based on Optical Character Recognition (OCR) technology makes use of image processing technology to extract and recognize characters of container codes automatically. On account of the advantages that such system doesn't need to attach any other equipment on container when recognizing, and its performance can be improved by means of manual operation through the user interface of computer terminal, it is developed rapidly and attached great importance by people increasingly.
In this thesis, the container AEI system based on OCR technology is investigated. First, the working principle of the system is introduced and the characteristics of container's original image is analyzed. Then the process procedures are discussed in detail, which include image preproccss, localization and threshold of container codes region, characters segmentation, recognition preproccss, feature extraction and recognition. In image preprocessing, image quality is improved by using mathematical morphology to remove background of the image, making gray-scale transformation to enhance contrast and smoothing processing to filter noise. After image preprocessed, its edge is detected, and some long lines in edge image are filtered, and then mathematical morphology is employed to remove edge noise. Considering the characteristic of characters arrayed concentrated, the method that how to make use of character edge and mathematical morphology to locate container codes is described. The gray image in characters area is converted to binary one by suitable threshold. The segmentation technology that combines the technologies of getting connected region and projecting can be used to segment characters. Finally, characters are recognized by utilizing moments to recognize alphabetic character and structure information of numeric character to recognize number.
The experiments' results show that the method of locating container codes is effective and the method of character recognition has some reference value.
本文研究的是基于光学字符识别技术的集装箱自动识别系统，简要介绍了系统的工作原理，分析了集装箱原始图像的特点，详细阐述了系统处理流程：图像预处理、箱号字符区域定位、箱号字符区域二值化及字符分割、识别预处理、特征提取和字符识别。本文运用形态学运算消除背景、进行灰度变换增强对比度和进行平滑过滤噪声来完成图像的预处理。对预处理后的图像进行边缘提取，先消除非字符边缘的长线条，再用形态学运算消除干扰边缘和噪声。针对字符排列相对集中的特点，详细介绍了如何利用边缘结合形态学定位箱号字符的方法来实现箱号字符的定位。选用合适的二值化方法完成字符区域的灰度图像到二值图像的转换。利用基于求连通区域与投影相结合的字符切分技术完成字符的分割。讨论了字符识别技术，实现了利用图像矩特征进行字符识别以及利用数字的结构特征识别数字。
实验表明，文中的箱号定位方法是有效的，字符识别方法亦具有一定的参考价值。
Container Automatic Equipment Identification (AEI) system can be widely applied to material circulation monitoring system in customs, to container management system in harbor bureau, container depot, and transportation industry, and to monitoring and management system in machining center, etc. Container AEI system based on Optical Character Recognition (OCR) technology makes use of image processing technology to extract and recognize characters of container codes automatically. On account of the advantages that such system doesn't need to attach any other equipment on container when recognizing, and its performance can be improved by means of manual operation through the user interface of computer terminal, it is developed rapidly and attached great importance by people increasingly.
In this thesis, the container AEI system based on OCR technology is investigated. First, the working principle of the system is introduced and the characteristics of container's original image is analyzed. Then the process procedures are discussed in detail, which include image preproccss, localization and threshold of container codes region, characters segmentation, recognition preproccss, feature extraction and recognition. In image preprocessing, image quality is improved by using mathematical morphology to remove background of the image, making gray-scale transformation to enhance contrast and smoothing processing to filter noise. After image preprocessed, its edge is detected, and some long lines in edge image are filtered, and then mathematical morphology is employed to remove edge noise. Considering the characteristic of characters arrayed concentrated, the method that how to make use of character edge and mathematical morphology to locate container codes is described. The gray image in characters area is converted to binary one by suitable threshold. The segmentation technology that combines the technologies of getting connected region and projecting can be used to segment characters. Finally, characters are recognized by utilizing moments to recognize alphabetic character and structure information of numeric character to recognize number.
The experiments' results show that the method of locating container codes is effective and the method of character recognition has some reference value.
引文
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[36]刘维一，盛益强，乔辉，方志良．特征点匹配法实现汽车牌照的快速识别．光电子·激光．2002，13(3)：274-276
[37]宋加涛，刘济林．车辆牌照上英文和数字字符的结构特征分析及提取．中国图象图形学报．2002，7(A)(9)：945-949
[38]王少杰，朱志刚，石定机，俞志和．货运列车车型车号自动分割和识别算法．模式识别与人工智能．1998，11(3)：328-334
[39]张玉姣，史忠科．一种新的车牌识别预处理算法．西北工业大学学报．2002，20(1)：83-86
[40]李小平，任江兴，杨德刚．车牌识别系统中若干问题的探讨．北京理工大学学报．2001，21(1)：116-119
[41]高庆吉，王晓华，赵为平．对粘连和缺损数字串分割的研究．模式识别与人工智能．2000，13(1)：99-102
[42]Ming-Kuei Hu. Visual pattern recognition by moment invariants. Information Theory, IEEE Transactions on , Volume: 8 Issue: 2 , Feb 1962. Page(s): 179-187
[43]Ozawa, H.; Nakagawa, T. A character image enhancement method from characters with various background images. Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on , 20-22 Oct. 1993. Page(s): 58-61
[44]Lienhart, R.; Wernicke, A. Localizing and segmenting text in images and videos. Circuits and Systems for Video Technology, IEEE Transactions on, Volume: 12 Issue: 4 , April 2002. Page(s): 256-268
[45]Hegt, H.A.; de la Haye, R.J.; Khan, N.A. A high performance license plate recognition system. Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on , Volume: 5 , 11-14 Oct. 1998. Page(s): 4357-4362 vol. 5
[46]Yuntao Cui; Qian Huang. Automatic license extraction from moving vehicles. Image Processing, 1997. Proceedings. International Conference on , Volume:3 , 26-29 Oct. 1997. Page(s): 126-129 vol. 3
[47]Naito, T.; Tsukada, T.; Yamada, K.; Kozuka, K.; Yamamoto, S. Robust recognition methods for inclined license plates under various illumination conditions outdoors. Intelligent Transportation Systems, 1999. Proceedings. 1999 IEEE/IEEJ/JSAI International Conference on , 5-8 Oct. 1999. Page(s): 697- 702
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[2]张运刚，雍力，李柏泉．集装箱自动识别系统概述．交通标准化．1999，3：33-35
[3]张庆年，凌斌．基于神经网络的集装箱箱号智能识别系统研究．武汉理工大学学报．2001，23(6)：51-53
[4]李小平，段锴，赵健龙．利用BP算法实现集装箱编号识别．北京理工大学学报．2001，21(3)：345-347
[5]章敏．集装箱装卸区集卡道口的自动化系统．上海港科技．1999，6：22-25
[6]免利斯托夫·西德曼．集装箱自动识别进展显著．高沈宁编译．世界标准化与质量管理．1991，12：31-32
[7]张坚，毛弘杰．集装箱箱号自动识别验核系统在口岸物流监控中的作用．中国海关．2000，12：39-40
[8]崔屹．图像处理与分析——数学形态学方法及应用．科学出版社，2000
[9]吴敏金．图像形态学．上海科学技术文献出版社，1991
[10]龚炜，石青云，程民德．数字空间中数学形态学——理论及应用．科学出版社，1997
[11]赵荣椿等．数字图像处理导论．西北工业大学出版社，1999
[12]夏良正．数字图像处理．东南大学出版社，1999
[13]向世明．Visual C++数字图像与图形处理．电子工业出版社，2002
[14]阮秋琦．数字图像处理学．电子工业出版社，2001
[15]王思贤，刘宗义，梅建新．低对比度图像目标分割的研究．武汉大学学保(自然科学版)．2000，45(5)：641-644
[16]谢鸣．基于形态学的车牌自动识别系统的研究．武汉理工大学硕士学位论文．2002
[17]历旭．基于神经网络的车牌识别系统的研究与设计．武汉理工大学硕士学位论文．2002
[18]沈瑛．身份证识别系统研究．西南交通大学硕士学位论文．2002
[19]黄新．汽车牌照自动识别系统中字符的分割和识别．南京航空航天大学硕士学位论文．2002
[20]周波．汽车牌照识别的初步研究．成都理工大学硕士学位论文．2002
[21]戴琰．基于网络数据库的汽车牌照自动识别系统．浙江大学硕士学位论文．2002
[22]甘雷．车辆牌照识别系统(LPRS)研究．北京工业大学硕士学位论文．2002
[23]牛欣．车辆牌照识别若干关键技术的研究．北京工业大学硕士学位论文．2000
[24]边肇祺．模式识别．第二版．清华大学出版社，2000
[25]王广宇．车辆牌照识别系统综述．郑州轻工业学院学报(自然科学版)．2001，16(2)：47-50
[26]张炘中．汉字识别技术．清华大学出版社，1992：31-57
[27]王耀明．图像的矩函数：原理、算法及应用．华东理工大学出版社，2002
[28]王晓红，赵荣椿．用矩特征进行光字符识别的一种新方法．计算机应用与软件．2001，18(12)：54-56
[29]Salvador Igual, I.; Andreu Garcia, G.; Perez Jimenez, A. Preprocessing and recognition of characters in container codes. Pattern Recognition, 2002. Proceedings. 16th International Conference on, Volume:3, 11-15 Aug. 2002. Page(s): 143-146 vol. 3
[30]Lui, H.C.; Lee, C.M.; Fang Gao. Neural network application to container number recognition. Computer Software and Applications Conference, 1990. COMPSAC 90. Proceedings., Fourteenth Annual International, 31 Oct.-2 Nov. 1990. Page(s): 190-195
[31]Mullot, R.; Olivier, C.; Bourdon, J.L.; Courtellemont, P.; Labiche, J.; Lecourtier, Y. Automatic extraction methods of container identity number and registration plates of cars. Industrial Electronics, Control and Instrumentation, 1991. Proceedings. IECON '91., 1991 International Conference on , 28 Oct.-1 Nov. 1991. Page(s): 1739-1744 vol. 3
[32]Lee, J.C.M. Automatic character recognition for moving and stationary vehicles and containers in real-life images. Neural Networks, 1999. IJCNN '99. International Joint Conference on, Volume: 4, 10-16 July 1999. Page(s): 2824-2828 vol. 4
[33]Lynch, M.R. Advances in digital recognition technologies. Security and Detection, 1995., European Convention on, 16-18 May 1995. Page(s): 77-80
[34]孙兆林．MATLAB 6.x图像处理．清华大学出版社，2002
[35]严国莉，黄山，李岱璋，尚建华．印刷体数字快速识别算法在身份证编号数字识别中的应用．计算机工程．2003，29(1)：178-179
[36]刘维一，盛益强，乔辉，方志良．特征点匹配法实现汽车牌照的快速识别．光电子·激光．2002，13(3)：274-276
[37]宋加涛，刘济林．车辆牌照上英文和数字字符的结构特征分析及提取．中国图象图形学报．2002，7(A)(9)：945-949
[38]王少杰，朱志刚，石定机，俞志和．货运列车车型车号自动分割和识别算法．模式识别与人工智能．1998，11(3)：328-334
[39]张玉姣，史忠科．一种新的车牌识别预处理算法．西北工业大学学报．2002，20(1)：83-86
[40]李小平，任江兴，杨德刚．车牌识别系统中若干问题的探讨．北京理工大学学报．2001，21(1)：116-119
[41]高庆吉，王晓华，赵为平．对粘连和缺损数字串分割的研究．模式识别与人工智能．2000，13(1)：99-102
[42]Ming-Kuei Hu. Visual pattern recognition by moment invariants. Information Theory, IEEE Transactions on , Volume: 8 Issue: 2 , Feb 1962. Page(s): 179-187
[43]Ozawa, H.; Nakagawa, T. A character image enhancement method from characters with various background images. Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on , 20-22 Oct. 1993. Page(s): 58-61
[44]Lienhart, R.; Wernicke, A. Localizing and segmenting text in images and videos. Circuits and Systems for Video Technology, IEEE Transactions on, Volume: 12 Issue: 4 , April 2002. Page(s): 256-268
[45]Hegt, H.A.; de la Haye, R.J.; Khan, N.A. A high performance license plate recognition system. Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on , Volume: 5 , 11-14 Oct. 1998. Page(s): 4357-4362 vol. 5
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