基于机器视觉的印刷条码质量检测系统研究
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摘要
条码具有广泛的应用领域。然而,在条码的印刷过程中,由于印刷机械精度和工艺等原因,印刷条码符号常会出现各种质量问题。传统的离线印制条码质量检测方法已经不能满足生产和市场的需要,利用机器视觉技术对印刷条码的质量进行自动检测已成为必然趋势。
本文针对条码技术的应用和印刷企业的实际生产需要,把机器视觉、条码自动识别、图像处理等技术与印刷生产相结合,对印刷条码质量检测系统进行了较全面的基础性研究。首先分析研究了印制条码质量在线检测系统与通用印品缺陷在线检测系统在硬件、软件实现中的异同,确定了系统的实现方案。重点分析了几种用于条码图像识别检测的经典图像处理算法,并提出了一种基于条码边缘特征的识别检测方法,实现了对大部分条码印刷质量检测项目的在线检测。开发了以模拟印刷实验平台为硬件平台、Visual C++6.0为软件平台的印刷条码质量在线检测系统。该系统能实时对印刷过程中的条码符号进行外观缺陷、空白区尺寸、条高、放大系数、译码正确性等7个检测项目的自动检测,并能对检测结果进行分析统计,发出警报信息。
本文设计的印刷条码质量检测系统基本满足了实时性要求,系统功能较全,操作简单方便,具有一定的实用价值。
Bar code is used in various fields. However, in the process of printing bar code, there are different kinds of quality problems due to the accuracy of machines and techniques. Since the traditional way of quality-checking can not satisfy the needs of production and the market, a new way based on machine vision has become a popular trend.
In this thesis, according to the practical needs of some printing enterprises and the application of bar code techniques, the author combines techniques of machine vision, automatic bar code recognition, image processing with printing to give a complete and basic study of the quality-checking system of printed bar code. First, this thesis analyzes the differences between the online checking system of printing bar code and the online checking system of the common printing deficiency in the practical use of software and hardware. Then, it sets up a plan to realize the system. It puts great emphasis on the analysis of several classic image-processing methods utilized in the inspection of bar code recognition and designs a checking and recognition system based on the features of bar code edge. This helps to realize the online quality-checking of most bar code and develops an online quality checking based on the hardware platform of virtual printing experiment and the software platform of Visual C++6.0. This system can automatically inspect the appearance defect, size of clear area, size of the bars, enlargement index, and the accuracy of recognition code at any time in the printing process. Besides, it can also analyzes the inspection results and carries out alarming information.
The quality-checking system of the printed bar code designed in this thesis satisfies the instant needs of production, and it has fairly prefect function and simple performance. Thus, it is of practical use.
本文针对条码技术的应用和印刷企业的实际生产需要,把机器视觉、条码自动识别、图像处理等技术与印刷生产相结合,对印刷条码质量检测系统进行了较全面的基础性研究。首先分析研究了印制条码质量在线检测系统与通用印品缺陷在线检测系统在硬件、软件实现中的异同,确定了系统的实现方案。重点分析了几种用于条码图像识别检测的经典图像处理算法,并提出了一种基于条码边缘特征的识别检测方法,实现了对大部分条码印刷质量检测项目的在线检测。开发了以模拟印刷实验平台为硬件平台、Visual C++6.0为软件平台的印刷条码质量在线检测系统。该系统能实时对印刷过程中的条码符号进行外观缺陷、空白区尺寸、条高、放大系数、译码正确性等7个检测项目的自动检测,并能对检测结果进行分析统计,发出警报信息。
本文设计的印刷条码质量检测系统基本满足了实时性要求,系统功能较全,操作简单方便,具有一定的实用价值。
Bar code is used in various fields. However, in the process of printing bar code, there are different kinds of quality problems due to the accuracy of machines and techniques. Since the traditional way of quality-checking can not satisfy the needs of production and the market, a new way based on machine vision has become a popular trend.
In this thesis, according to the practical needs of some printing enterprises and the application of bar code techniques, the author combines techniques of machine vision, automatic bar code recognition, image processing with printing to give a complete and basic study of the quality-checking system of printed bar code. First, this thesis analyzes the differences between the online checking system of printing bar code and the online checking system of the common printing deficiency in the practical use of software and hardware. Then, it sets up a plan to realize the system. It puts great emphasis on the analysis of several classic image-processing methods utilized in the inspection of bar code recognition and designs a checking and recognition system based on the features of bar code edge. This helps to realize the online quality-checking of most bar code and develops an online quality checking based on the hardware platform of virtual printing experiment and the software platform of Visual C++6.0. This system can automatically inspect the appearance defect, size of clear area, size of the bars, enlargement index, and the accuracy of recognition code at any time in the printing process. Besides, it can also analyzes the inspection results and carries out alarming information.
The quality-checking system of the printed bar code designed in this thesis satisfies the instant needs of production, and it has fairly prefect function and simple performance. Thus, it is of practical use.
引文
【1】Pavlidis T, Swartz J, Wang Y P. Fundamental of bar code information theory [J]. IEEE Computer. Apr, 1990, 74-86.
【2】中国物品编码中心.条码技术与应用[M].北京:清华大学出版社,2003
【3】张成海,张铎.现代自动识别技术与应用[M].北京:清华大学出版社,2003
【4】卢瑞文.自动识别技术[M].北京:化学工业出版社,2005
【5】http://www.willopto.com
【6】李金哲,柱军营,光增满等.条形码自动识别技术[M].北京:国防工业出版社,1991
【7】韦元华,舟子.条形码技术与应用[M].北京:中国纺织出版社,2003
【8】张铎, 王耀球. 条码技术与电子数据交换[M]. 北京: 中国铁道出版社, 1998.
【9】http://www.foodqs.com/news/gnspzs01/2006311103935.htm
【10】鲁继文,张二虎,段刚龙.基于图像处理的印品质量在线检测[J].印刷杂志 2005,227:49-51
【11】GB 12904-2003,商品条码[S]
【12】GB/T 18348—2001,商品条码符号印制质量的检验[S]
【13】GB/T 14258—1993,条码符号印制质量的检验[S]
【14】GB/T 12905-2000,条码术语[S]
【15】薛延学,张二虎,吴学毅.基于计算机视觉的印刷包装品缺陷检测系统[J].包装工程, 2004,25(5):64-66
【16】刘宁钟,杨静宇.基于波形分析的二维条码识别[J].计算机研究与发展,2004,41(3):463-469
【17】刘宏伟,苗东,李志刚,韦有华.二维条码的识别方法[J].微计算机信息(测控自动化),2004,20(4):72-73
【18】何斌, 马天予, 王运坚等. Visual C++ 数字图像处理[M]. 北京: 人民邮电出版社, 2001.
【19】 刘宁钟,杨静宇.基于中点检测的二维条码识别[J].小型微型计算机系统,2004,25(2):283-286
【20】姚俊,范永法.基于 DSP 的有复杂背景的条码图像自动识别[J].河海大学常州分校学报,2004,18(2):14-18
【21】姚俊,范永法. 基于模板匹配的有复杂背景的条码图像区域分割[J].河海大学常州分校学报,2003,19(4):24-27
【22】王雅静.基于图像处理的 EAN-13 条码识别算法[J].山东理工大学学报(自然科学版),2005,19(4):14-18
【23】沙毅,曹英禹,王经武,盛国松.基于图形处理技术的工件长度在线测量[J].东北大学学报(自然科学版),2005,26(10):957-959
【24】甘岚,刘宁钟.基于亚像素边缘检测的二维条码识别[J].计算机工程,2003,29(22):155-157
【25】刘宁钟,杨静宇.基于傅立叶变换的二维条码识别[J].中国图象图形学报,2003,8(8):877-882
【26】S J Shellhammer, D P Goren. Novel signal processing techniques in barcode scanning[J]. IEEE Robotics & Automation Magazine, 1999,6(1):57-65
【27】郭艳萍,周海彬.数字图像处理技术在条码识别中的应用[J].河海大学常州分校学报,2002,16(3):15-18
【28】杨枝灵,王开.Visual C++数字图像获取处理及实践应用[M],北京 :人民邮电出版社,2003
【29】阮秋琦.数字图像处理学[M],北京:电子工业出版社,2001
【30】王新成.高级图像处理技术[M].北京:中国科学技术出版社,2001
【31】容观澳.计算机图像处理[M]. 北京: 清华大学出版社, 2000.
【32】孙即祥.模式识别中的特征提取与计算机视觉不变量[M], 北京:国防工业出版社,2001
【33】Normand N, Viard-Guadin C. Two Dimensional Bar Code Reader .Proceedings of SPIE,1994:125-132
【34】Joseph E, Pavlidis T. Bar Code Waveform Recognition Using Peak Locations. IEEE Trans. PAMI, 1994, 16(6):630-640
【35】郑南宁.计算机视觉与模式识别[M],北京:国防工业出版社,1998
【36】Huertas A, Medioni G. Detection of Intensity Changes with Subpixel Accuracy Using Laplacian-Gaussian Masks. IEEE Trans. PAMI,1986,8(5): 651-664
【37】郑河荣,熊丽荣,王天舟.基于 HOUGH 变换的二维条码图象矫正[J].浙江工业大学学报,2003,31(2):169-172
【2】中国物品编码中心.条码技术与应用[M].北京:清华大学出版社,2003
【3】张成海,张铎.现代自动识别技术与应用[M].北京:清华大学出版社,2003
【4】卢瑞文.自动识别技术[M].北京:化学工业出版社,2005
【5】http://www.willopto.com
【6】李金哲,柱军营,光增满等.条形码自动识别技术[M].北京:国防工业出版社,1991
【7】韦元华,舟子.条形码技术与应用[M].北京:中国纺织出版社,2003
【8】张铎, 王耀球. 条码技术与电子数据交换[M]. 北京: 中国铁道出版社, 1998.
【9】http://www.foodqs.com/news/gnspzs01/2006311103935.htm
【10】鲁继文,张二虎,段刚龙.基于图像处理的印品质量在线检测[J].印刷杂志 2005,227:49-51
【11】GB 12904-2003,商品条码[S]
【12】GB/T 18348—2001,商品条码符号印制质量的检验[S]
【13】GB/T 14258—1993,条码符号印制质量的检验[S]
【14】GB/T 12905-2000,条码术语[S]
【15】薛延学,张二虎,吴学毅.基于计算机视觉的印刷包装品缺陷检测系统[J].包装工程, 2004,25(5):64-66
【16】刘宁钟,杨静宇.基于波形分析的二维条码识别[J].计算机研究与发展,2004,41(3):463-469
【17】刘宏伟,苗东,李志刚,韦有华.二维条码的识别方法[J].微计算机信息(测控自动化),2004,20(4):72-73
【18】何斌, 马天予, 王运坚等. Visual C++ 数字图像处理[M]. 北京: 人民邮电出版社, 2001.
【19】 刘宁钟,杨静宇.基于中点检测的二维条码识别[J].小型微型计算机系统,2004,25(2):283-286
【20】姚俊,范永法.基于 DSP 的有复杂背景的条码图像自动识别[J].河海大学常州分校学报,2004,18(2):14-18
【21】姚俊,范永法. 基于模板匹配的有复杂背景的条码图像区域分割[J].河海大学常州分校学报,2003,19(4):24-27
【22】王雅静.基于图像处理的 EAN-13 条码识别算法[J].山东理工大学学报(自然科学版),2005,19(4):14-18
【23】沙毅,曹英禹,王经武,盛国松.基于图形处理技术的工件长度在线测量[J].东北大学学报(自然科学版),2005,26(10):957-959
【24】甘岚,刘宁钟.基于亚像素边缘检测的二维条码识别[J].计算机工程,2003,29(22):155-157
【25】刘宁钟,杨静宇.基于傅立叶变换的二维条码识别[J].中国图象图形学报,2003,8(8):877-882
【26】S J Shellhammer, D P Goren. Novel signal processing techniques in barcode scanning[J]. IEEE Robotics & Automation Magazine, 1999,6(1):57-65
【27】郭艳萍,周海彬.数字图像处理技术在条码识别中的应用[J].河海大学常州分校学报,2002,16(3):15-18
【28】杨枝灵,王开.Visual C++数字图像获取处理及实践应用[M],北京 :人民邮电出版社,2003
【29】阮秋琦.数字图像处理学[M],北京:电子工业出版社,2001
【30】王新成.高级图像处理技术[M].北京:中国科学技术出版社,2001
【31】容观澳.计算机图像处理[M]. 北京: 清华大学出版社, 2000.
【32】孙即祥.模式识别中的特征提取与计算机视觉不变量[M], 北京:国防工业出版社,2001
【33】Normand N, Viard-Guadin C. Two Dimensional Bar Code Reader .Proceedings of SPIE,1994:125-132
【34】Joseph E, Pavlidis T. Bar Code Waveform Recognition Using Peak Locations. IEEE Trans. PAMI, 1994, 16(6):630-640
【35】郑南宁.计算机视觉与模式识别[M],北京:国防工业出版社,1998
【36】Huertas A, Medioni G. Detection of Intensity Changes with Subpixel Accuracy Using Laplacian-Gaussian Masks. IEEE Trans. PAMI,1986,8(5): 651-664
【37】郑河荣,熊丽荣,王天舟.基于 HOUGH 变换的二维条码图象矫正[J].浙江工业大学学报,2003,31(2):169-172