JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Angle Invariant and Noise Robust Barcode Detection System
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
  • Journal title : Journal of KIISE
  • Volume 42, Issue 7,  2015, pp.868-877
  • Publisher : Korean Institute of Information Scientists and Engineers
  • DOI : 10.5626/JOK.2015.42.7.868
 Title & Authors
Angle Invariant and Noise Robust Barcode Detection System
Park, Dongjin; Jun, Kyungkoo;
 
 Abstract
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.
 Keywords
barcode detection;probabilistic hough transform;frequency component analysis;multiply detection;noise filtering;
 Language
Korean
 Cited by
 References
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. crossref(new window)

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. crossref(new window)

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: https://github.com/zxing/zxing/(downloaded 2015, Mar. 26)