[1]陈星[],徐迎晖[],肖青海[][]. QR码印刷品缺陷检测[J].计算机技术与发展,2015,25(10):191-194.
　CHEN Xing[],XU Ying-hui[],XIAO Qing-hai[][]. Defect Detection of Printed QR Code Image[J].,2015,25(10):191-194.
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 QR码印刷品缺陷检测()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
25
期数:
2015年10期
页码:
191-194
栏目:
应用开发研究
出版日期:
2015-10-10

文章信息/Info

Title:
 Defect Detection of Printed QR Code Image
文章编号:
1673-629X（2015)10-0191-04
作者:
 陈星[1];  徐迎晖[1];  肖青海[2][3]
1. 广东工业大学 自动化学院；2.北京邮电大学 计算机学院；3. 信息工程大学 密码工程学院
Author(s):
 CHEN Xing[1] ; XU Ying-hui[1];  XIAO Qing-hai[2][3]
关键词:
 ; QR码; 缺陷检测; 邻域模板; 区域矫正; 图像匹配
Keywords:
 ; QR code; defect detection; neighborhood model; projective transformation; image matching
分类号:
TP391.41
文献标志码:
A
摘要:
 针对QR码印刷品中出现的黑白拉线或黑白块等印刷问题，文中提出了一种有效的QR码印刷品缺陷检测的解决方案。将机器视觉应用到QR码印刷制品的缺陷检测中去，可以自动识别带有缺陷的样本，从而解决了人工检测所带来的问题。结合HALCON的条码识读和图像处理相关算子，以Visual C++编程实现解决方案中的邻域模板生成、条码区域矫正和图像匹配等关键步骤，来实现对QR码印刷品中出现的黑白拉线或黑白块等印刷问题进行有效的检测。实验结果表明，此方案能从测试样本图像中自动提取条码，并且快速而又精确地完成图像匹配，有效地检测出印刷缺陷，并具有良好的鲁棒性。
Abstract:
 Propose an effective solution of the defect detection of printed QR code image to resolve the problems of print quality than white line,black line,white block or black block appears in printed QR code image. Applying machine vision to the QR code defect in-spection of printing products,can automatically identify defective sample,so as to solve the problem brought by the artificial detection. With the reference functions of bar code decoding and image processing in HALCON,the solution uses Visual C++ to accomplish these key steps of generating neighborhood model,homogeneous projective transformation and image matching,to implement the effective de-tection for QR code printed in black and white arrows or piece of printing problems,such as black and white. The experimental results show that the solution can automatically extract bar code in test sample,quickly and accurately execute image matching,effectively detect printed defect and has good robustness.

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更新日期/Last Update: 2015-11-13