Angle Invariant and Noise Robust Barcode Detection System

기울기와 노이즈에 강인한 바코드 검출 시스템

  • 박동진 (인천대학교 임베디드시스템공학과) ;
  • 전경구 (인천대학교 임베디드시스템공학과)
  • Received : 2015.01.13
  • Accepted : 2015.05.26
  • Published : 2015.07.15


The barcode area extraction from images has been extensively studied, and existing methods exploit frequency characteristics or depend on the Hough transform (HT). However, the slantedness of the images and noise affects the performance of these approaches. Moreover, it is difficult to deal with the case where an image contains multiple barcodes. We therefore propose a barcode detection algorithm that is robust under such unfavorable conditions. The pre-processing step implements a probabilistic Hough transform to determine the areas that contain barcodes with a high probability, regardless of the slantedness, noise, and the number of instances. Then, a frequency component analysis extracts the barcodes. We successfully implemented the proposed system and performed a series of barcode extraction tests.

영상에서 바코드 영역을 검출하는 다양한 방식들이 연구되어 왔다. 기존 방식들은 주파수 성분 특징을 이용하거나, Hough transform (HT)을 이용하여 바코드 영역을 검출한다. 하지만 이 방식들은 바코드의 기울기와 노이즈에 영향을 받는다. 또한 여러 개의 바코드가 있는 경우 정확히 검출하지 못한다. 본 논문에서는 바코드의 기울기와 노이즈에 강인하고, 복수 개의 바코드를 검출할 수 있는 방식을 제안한다. 우리는 전처리 단계로 Probabilistic Hough transform (PHT)를 이용하여 바코드 기울기, 노이즈, 그리고 개수에 상관없이 바코드가 존재할 가능성이 높은 영역을 추출한 후, 주파수 성분 분석을 통해 바코드를 찾아낸다. 구현된 시스템의 성능분석을 통해 다양한 환경에서 바코드 추출이 가능함을 확인했다.



Supported by : 정보통신산업진흥원


  1. D. Chai, and F. Hock, "Locating and decoding EAN-13 barcodes from images captured by digital cameras," ICICS, Vol. 5, pp. 1595-1599, 2005.
  2. A. Zamberletti, I. Gallo, and S. Albertini, "Robust angle invariant 1D barcode detection," Second IAPR Asian Conference on Pattern Recognition, pp. 160-164, Nov, 2013.
  3. R. O Duda, and P. E Hart, "Use of hough transformation to detect line and curves in picture," Communications of the ACM, Vol. 15, No. 1, pp. 11-15, Jun. 1972.
  4. M. Katona, and L. G. Nyul, "A novel method for accurate and efficient barcode detection with morphological operations," 8th International Conference on Signal Image Technology (SITIS 2012), pp. 307-314, Nov. 2012.
  5. H. Hu, W. Xu, and Q. Huang, "A 2D barcode extraction method based on texture direction analysis," Fifth International Conference on Image and Graphics, pp. 759-762, 2009.
  6. L. Qiaoling, L. Xiaochao, Z. Mei, and Z. Jun, "The multi-QR codes extraction method in illegible image based on contour tracing," 2011 IEEE International Conference on Anti-Counterfeiting, Security and Identification, pp. 51-56, Jun. 2011.
  7. H. Kato, K. T. Tan, and D. Chai, "Development of a novel finder pattern for effective color 2d-barcode detection," ISPA '08. International Symposium on Parallel and Distributed Processing with Applications, pp. 1006-1013, Dec. 2008.
  8. Y. Zheng, H. Li, and D. Doermann, "A parallel-line detection algorithm based on HMM decoding," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 27, No. 5, pp. 777-792, May. 2005.
  9. A. Borkar, M. Hayes, and M. T. Smith, "Polar randomized hough transform for lane detection using loose constraints of parallel lines," 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1037-1040, May. 2011.
  10. G. Klimek, and Z. Vamossy, "QR Code detection using parallel lines," 2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI), pp. 477-481, Nov. 2013.
  11. P. Bodnar, and L. G. Nyul, "Improving Barcode Detection with Combination of Simple Detectors," 2012 Eighth International Conference on Signal Image Technology and Internet Based Systems (SITIS), pp. 300-306, Nov. 2012.
  12. C. Galambos, J. Matas, and J. Kittler, "Progressive probabilistic Hough transform for line detection," 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 1, pp. 66- 71, Feb. 1999.
  13. John Canny, "A computational approach to edge detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 8, No. 6, pp. 679-698, Nov. 1986.
  14. A. Zamberletti, I. Gallo, M. Carullo, and E. Binaghi, "Neural Image Restoration For Decoding 1-D Barcodes Using Common Camera Phones," Computer Vision, Imaging and Computer Graphics, Theory and Applications, Springer Berlin Heidelberg, 2011.
  15. S. Wachenfeld, S. Terlunen, and X. Jiang, "Robust 1-D barcode recognition on camera phones and mobile product information display," Mobile Multimedia Processing, Vol. 5960, pp. 53-69, 2010.
  16. Zebra Crossing [Online]. Avaliable: 2015, Mar. 26)