QRCode二维条码编译码及自动识别技术的研究
摘要
随着全球信息化的发展,人们对条码技术的需求层次不断提高,尤其是需要在有限的面积上表示更多的信息量。在这种需求下,二维条码孕育而生,它在各个领域得到了广泛应用。二维条码本身所具有的高容量、高密度、纠错能力强、安全强度高等特点使得二维条码作为信息的载体在信息自动化领域发挥着越来越重要的作用。二维条码的广泛应用要求条码的译码更加简单方便,即使没有专用译码设备也能够使用二维条码,这主要依靠相机和摄像头等图像采集设备来实现。本文针对用图像采集设备得到的符号图像进行译码的要求,提出了一个QR Code二维条码系统。大体内容如下:
本文第一部分,首先介绍了二维条码和QR Code二维条码的基础知识及特点,选取QR Code二维条码作为研究对象。由于它有专有的中国汉字字符集,所以相对与其它条码来讲,更适合我国的实际应用情况。第二部分是编码系统的研究。这部分探讨QR Code二维条码编码系统的设计,重点研究的是编码模式选择的算法,改进了国家标准GB/T 18284-2000给出的参考算法,改进后的算法在实验中取得了较好的效果。第三部分是译码系统的研究。首先是图像预处理部分的研究,包括灰度化、中值滤波,图像二值化算法等。根据实际情况,选取较为合适的图像处理方法。在译码系统的研究中,重点是符号图像自动识别技术的研究。包括条码图像定位算法和采样网格建立算法。本系统定位算法充分利用了QR Code二维条码符号的特点,即三个位置探测图形,采用扫描线算法,对符号中的位置探测图形进行扫描,最后求得位置探测图形的中心坐标点,完成符号的定位。由于图像旋转、形变和条码图像本身的特点等因素影响,扫描线在扫描时会出现很多干扰因素,即本身并不属于位置探测图形的区域也出现满足位置探测图形模块比例的扫描线的情况,如何对这些扫描线进行有效的筛选,剔除可能不属于位置探测图形的扫描线算法也是研究的重点。本文第四部分是关于整个编译码系统的实现。分别介绍了如何实现编码系统和译码系统。详细介绍了编码和译码系统中包含的子模块,以及各个模块之间的关系,最后附上的是系统主要部分的程序流程图。最后一部分是对编译码系统有效性测试。
结果表明,在Visual c++.net平台上实现的条码的编码和译码系统是有效的。编译码系统均能有效正确的实现信息的编码和译码。
As the global information developing, people request for improved barcode technology. It's required that presenting more information in limited area. As the requirement came out, two-dimensional (2D) symbol technology was proposed and in general use. Two-dimensional (2D) Barcode has played an important role in the information automation field because of its higher capacity, higher density, more powerful error-correction ability and higher security ability. The Recognition Tech- nology of 2D is to be asked more simple and easier because of its wider appli- cation, and even no dedicated decoding equipments, it can also be achieved with collecting 2D bar code images with camera. This paper aiming at implementing decoding of images collected by camera, proposed a coding and decoding system. The content as bellows:
The paper introduced basis of knowledge and characteristics of two dimensi- onal barcode and QRCode in the first part and chose QRCode as object of study. QRCode had Chinese Character Set, so that it was more suitable for Chinese situa- tion compared with other 2D barcode. And the second part of paper was about re- search of coding system. Discussed the design of coding system focused on deter- mination of coding mode. Based on the reference algorithm of GB/T 18284-2000, made some improving, and achieved good results. The third part of paper was about research of decoding system. First introduced how to process the collected barcode images with image processing methods including median filtering, image binarization and so on. According to the actual situation, chose a suitable method. The focus of decoding system research was automatic identify- cation, including locating and grid building arithmetic of code symbol. The symbol locating arithmetic of QRCode was fully use of three Finder Patterns. Scanned three finder patterns and then picked up the real scan line through three finder patterns in order to calcu- late the center coordinates and finally finished symbol locating. Because of impact of rotating, deformatiom and features of symbol image itself, when scanned symbol image, there might be some scan lines which was not belong to the area of finder patters. So How to judge these scan lines and pick up the real lines accurately was also a focus of research. The forth part of paper was about the implement of the whole system. It introduced how to implement coding and decod- ing system. And introduce the submodule of each system and the relationship among them in detail. And finally, there were some main flow charts of system. And the last part was the effectiveness test.
The result of research on Visual c++.net platform showed the system of coding and decoding is effective. The coding system can code accurately and decoding system also decode accurately.
本文第一部分,首先介绍了二维条码和QR Code二维条码的基础知识及特点,选取QR Code二维条码作为研究对象。由于它有专有的中国汉字字符集,所以相对与其它条码来讲,更适合我国的实际应用情况。第二部分是编码系统的研究。这部分探讨QR Code二维条码编码系统的设计,重点研究的是编码模式选择的算法,改进了国家标准GB/T 18284-2000给出的参考算法,改进后的算法在实验中取得了较好的效果。第三部分是译码系统的研究。首先是图像预处理部分的研究,包括灰度化、中值滤波,图像二值化算法等。根据实际情况,选取较为合适的图像处理方法。在译码系统的研究中,重点是符号图像自动识别技术的研究。包括条码图像定位算法和采样网格建立算法。本系统定位算法充分利用了QR Code二维条码符号的特点,即三个位置探测图形,采用扫描线算法,对符号中的位置探测图形进行扫描,最后求得位置探测图形的中心坐标点,完成符号的定位。由于图像旋转、形变和条码图像本身的特点等因素影响,扫描线在扫描时会出现很多干扰因素,即本身并不属于位置探测图形的区域也出现满足位置探测图形模块比例的扫描线的情况,如何对这些扫描线进行有效的筛选,剔除可能不属于位置探测图形的扫描线算法也是研究的重点。本文第四部分是关于整个编译码系统的实现。分别介绍了如何实现编码系统和译码系统。详细介绍了编码和译码系统中包含的子模块,以及各个模块之间的关系,最后附上的是系统主要部分的程序流程图。最后一部分是对编译码系统有效性测试。
结果表明,在Visual c++.net平台上实现的条码的编码和译码系统是有效的。编译码系统均能有效正确的实现信息的编码和译码。
As the global information developing, people request for improved barcode technology. It's required that presenting more information in limited area. As the requirement came out, two-dimensional (2D) symbol technology was proposed and in general use. Two-dimensional (2D) Barcode has played an important role in the information automation field because of its higher capacity, higher density, more powerful error-correction ability and higher security ability. The Recognition Tech- nology of 2D is to be asked more simple and easier because of its wider appli- cation, and even no dedicated decoding equipments, it can also be achieved with collecting 2D bar code images with camera. This paper aiming at implementing decoding of images collected by camera, proposed a coding and decoding system. The content as bellows:
The paper introduced basis of knowledge and characteristics of two dimensi- onal barcode and QRCode in the first part and chose QRCode as object of study. QRCode had Chinese Character Set, so that it was more suitable for Chinese situa- tion compared with other 2D barcode. And the second part of paper was about re- search of coding system. Discussed the design of coding system focused on deter- mination of coding mode. Based on the reference algorithm of GB/T 18284-2000, made some improving, and achieved good results. The third part of paper was about research of decoding system. First introduced how to process the collected barcode images with image processing methods including median filtering, image binarization and so on. According to the actual situation, chose a suitable method. The focus of decoding system research was automatic identify- cation, including locating and grid building arithmetic of code symbol. The symbol locating arithmetic of QRCode was fully use of three Finder Patterns. Scanned three finder patterns and then picked up the real scan line through three finder patterns in order to calcu- late the center coordinates and finally finished symbol locating. Because of impact of rotating, deformatiom and features of symbol image itself, when scanned symbol image, there might be some scan lines which was not belong to the area of finder patters. So How to judge these scan lines and pick up the real lines accurately was also a focus of research. The forth part of paper was about the implement of the whole system. It introduced how to implement coding and decod- ing system. And introduce the submodule of each system and the relationship among them in detail. And finally, there were some main flow charts of system. And the last part was the effectiveness test.
The result of research on Visual c++.net platform showed the system of coding and decoding is effective. The coding system can code accurately and decoding system also decode accurately.
引文
[1]张成海.QRCode二维条码.北京:中国标准出版社,2000.
[2]Pavlidis T,Swartz J,Wang Y P.Fundanmentals of bar code information theory.IEEE Computer,1990,23(4):74-86.
[3]Pavlidis T,Swartz J,Wang Y P.Information encoding with two-dimensional bar code.IEEE Computer,1992,27(6):18-27.
[4]Reiley D J.Polarization of barcode readers.Opt Eng,1998,37(2):688-695.
[5]娇运起,张成海.二维条码技术.北京:中国物价出版社,1996.12.
[6]范旭.条码技术的发展-浅谈二维条码.标准化报道,1999,20(6):40-42.
[7]陈晓平.条码印刷技术.北京:清华大学出版社,1993.
[8]薛红,薛红军,邹彦卿.二维条码在车辆管理系统中的应用研究.计算机工程,2002,28(6):211-213.
[9]胡向东.二维条码技术及其在电子邮票中的应用,计算机工程应用.2001,16:48-49,62.
[10]袁彬.基于二维条码和智能手机的无线身份认证系统:[硕士学位论文].大连:大连理工大学,2006.
[11]GB/T 18284-2000,快速响应矩阵码国家标准.
[12]AMI,ITS/97/001,International symbology specification-QR code.
[13]杨军,刘艳,杜彦蕊.关于二维码的研究和应用.应用科技,2002,29(11):11-13.
[14]中国物品编码中心.QR Code二维码技术与应用.第一版.北京:中国标准出版社.2001.
[15]Vicky Waltz.A vision of picture-perfect packaging.Machine Design;Cleveland;Oct 2001.
[16]Leo Rakowski.Getting a read on 3D bar codes Modern Machine Shop;Cincinnati;Feb 2001.
[17]Bert Moore.2D:Critical data in small packages.Materia Handling Engineering;Cleveland;Aug 1999.
[18]Gary A Mintchell.Vision systems:See new technology brin lower prices.Control Engineering;Barrington;Jun 1999.
[19]Lin S.Daniel J C.Error Control Coding:Fundamentals and Applications.Prentice-Hall.1983
[20]王新梅,肖国镇.纠错码原理与方法.西安:电子科技大学出版社.2001.
[21]周长发.精通Visual c++.net图像处理编程.北京:电子工业出版社.2002.
[22]卡斯特曼,朱志刚等译.数字图像处理.北京:电子工业出版社,2002.
[23]欧阳伟.QR二维条码自动识别系统的研究与实现:[硕士学位论文].上海:复旦大学,2006.
[24]唐良瑞,马全明等.图像处理使用技术.北京:化学工业出版社,2002
[25]邢藏菊,王守觉,邓浩江,罗予晋.一种基于极值中值的新型滤波算法[J].中国图像图形学报,2001,6A(6):533-536.
[26]Makoto Nagao,Takashi Matsnyama.Edge Preserving Smoothing.Computer Graphics and Image Processing,1979,9:394-407.
[27]刘兴伟,殷国富,罗小宾,胡晓兵.工程扫描图的一种新型的自适应中值滤波算法.中国机械工程,2002,13(5):403-405.
[28]朱菊华,杨新,李俊.一种改进的自适应保细节中值滤波算法.计算机工程与应用,2001,3:93-95.
[29]Refael C.Gonzalez,Richard E.Woods,Digital Image Processing(Second Edition).北京:电子工业出版社,2005
[30]张远朋,董海等.计算机图像处理技术基础.北京:北京大学出版社,1996.
[31]胡家忠.计算机文字识别技术.北京:气象出版社.1994
[32]N.Ostu.A Threshold Selection Method Form Gray-Level Histograms.IEEE Transactions on Systems,Man,and Cybernetics.1979,9(1):62-66
[33]Sang Uk Lee,Seok Yook Chung.A comparative performance study of several global thresholding techniques for segmentation.Computer Version,Graphics,and Image Understanding,1990,50(2):171-190.
[34]W.Niblack.An Introduction to Digital Image Processing.Prentice Hall,Englewood Cliffs,NJ,1986:115-116.
[35]Duda,R.O.,P.E.Hart.Use of the Hough Transform to Detect Lines and Curves in Pictures.Communications of the ACM,1972,15:11-15.
[36]Pui-Kin Ser,Wan-Chi Siu.A New Generalized Hough Transform for the Detection of Irregular Objects.Journal of Visual Communication and Image Representation.1995,6(2):256-264.
[37]YangYing,TanBisi.Applications of the Extended Hough Transform in Pattern Recognition.中南民族学院学报(自然科学版).2000,19(4):10-13.
[38]M.Atiquzzaman.Multiresolution Hough Transform-An Efficient Method of 39 Detecting Patterns in Images.IEEE Transactions on Pattern Analysis and Machine Intelligence.1992,14(11):1090-1095.
[40]夏良正.数字图像处理.南京:东南大学出版社,1999.
[41]Davenport W B,Root W L.An Introduction to the Theory of Randon Signals and Noise.New York:McGraw-Hill.1958.
[42]王立,常青等.Radon变换在低信噪比图像中的线段检测.红外与激光.2003.
[43]李军宏,潘泉,张洪才等.基于Radon变换的图像识别研究.计算机应用研究.2004,5:207-208,212.
[2]Pavlidis T,Swartz J,Wang Y P.Fundanmentals of bar code information theory.IEEE Computer,1990,23(4):74-86.
[3]Pavlidis T,Swartz J,Wang Y P.Information encoding with two-dimensional bar code.IEEE Computer,1992,27(6):18-27.
[4]Reiley D J.Polarization of barcode readers.Opt Eng,1998,37(2):688-695.
[5]娇运起,张成海.二维条码技术.北京:中国物价出版社,1996.12.
[6]范旭.条码技术的发展-浅谈二维条码.标准化报道,1999,20(6):40-42.
[7]陈晓平.条码印刷技术.北京:清华大学出版社,1993.
[8]薛红,薛红军,邹彦卿.二维条码在车辆管理系统中的应用研究.计算机工程,2002,28(6):211-213.
[9]胡向东.二维条码技术及其在电子邮票中的应用,计算机工程应用.2001,16:48-49,62.
[10]袁彬.基于二维条码和智能手机的无线身份认证系统:[硕士学位论文].大连:大连理工大学,2006.
[11]GB/T 18284-2000,快速响应矩阵码国家标准.
[12]AMI,ITS/97/001,International symbology specification-QR code.
[13]杨军,刘艳,杜彦蕊.关于二维码的研究和应用.应用科技,2002,29(11):11-13.
[14]中国物品编码中心.QR Code二维码技术与应用.第一版.北京:中国标准出版社.2001.
[15]Vicky Waltz.A vision of picture-perfect packaging.Machine Design;Cleveland;Oct 2001.
[16]Leo Rakowski.Getting a read on 3D bar codes Modern Machine Shop;Cincinnati;Feb 2001.
[17]Bert Moore.2D:Critical data in small packages.Materia Handling Engineering;Cleveland;Aug 1999.
[18]Gary A Mintchell.Vision systems:See new technology brin lower prices.Control Engineering;Barrington;Jun 1999.
[19]Lin S.Daniel J C.Error Control Coding:Fundamentals and Applications.Prentice-Hall.1983
[20]王新梅,肖国镇.纠错码原理与方法.西安:电子科技大学出版社.2001.
[21]周长发.精通Visual c++.net图像处理编程.北京:电子工业出版社.2002.
[22]卡斯特曼,朱志刚等译.数字图像处理.北京:电子工业出版社,2002.
[23]欧阳伟.QR二维条码自动识别系统的研究与实现:[硕士学位论文].上海:复旦大学,2006.
[24]唐良瑞,马全明等.图像处理使用技术.北京:化学工业出版社,2002
[25]邢藏菊,王守觉,邓浩江,罗予晋.一种基于极值中值的新型滤波算法[J].中国图像图形学报,2001,6A(6):533-536.
[26]Makoto Nagao,Takashi Matsnyama.Edge Preserving Smoothing.Computer Graphics and Image Processing,1979,9:394-407.
[27]刘兴伟,殷国富,罗小宾,胡晓兵.工程扫描图的一种新型的自适应中值滤波算法.中国机械工程,2002,13(5):403-405.
[28]朱菊华,杨新,李俊.一种改进的自适应保细节中值滤波算法.计算机工程与应用,2001,3:93-95.
[29]Refael C.Gonzalez,Richard E.Woods,Digital Image Processing(Second Edition).北京:电子工业出版社,2005
[30]张远朋,董海等.计算机图像处理技术基础.北京:北京大学出版社,1996.
[31]胡家忠.计算机文字识别技术.北京:气象出版社.1994
[32]N.Ostu.A Threshold Selection Method Form Gray-Level Histograms.IEEE Transactions on Systems,Man,and Cybernetics.1979,9(1):62-66
[33]Sang Uk Lee,Seok Yook Chung.A comparative performance study of several global thresholding techniques for segmentation.Computer Version,Graphics,and Image Understanding,1990,50(2):171-190.
[34]W.Niblack.An Introduction to Digital Image Processing.Prentice Hall,Englewood Cliffs,NJ,1986:115-116.
[35]Duda,R.O.,P.E.Hart.Use of the Hough Transform to Detect Lines and Curves in Pictures.Communications of the ACM,1972,15:11-15.
[36]Pui-Kin Ser,Wan-Chi Siu.A New Generalized Hough Transform for the Detection of Irregular Objects.Journal of Visual Communication and Image Representation.1995,6(2):256-264.
[37]YangYing,TanBisi.Applications of the Extended Hough Transform in Pattern Recognition.中南民族学院学报(自然科学版).2000,19(4):10-13.
[38]M.Atiquzzaman.Multiresolution Hough Transform-An Efficient Method of 39 Detecting Patterns in Images.IEEE Transactions on Pattern Analysis and Machine Intelligence.1992,14(11):1090-1095.
[40]夏良正.数字图像处理.南京:东南大学出版社,1999.
[41]Davenport W B,Root W L.An Introduction to the Theory of Randon Signals and Noise.New York:McGraw-Hill.1958.
[42]王立,常青等.Radon变换在低信噪比图像中的线段检测.红外与激光.2003.
[43]李军宏,潘泉,张洪才等.基于Radon变换的图像识别研究.计算机应用研究.2004,5:207-208,212.