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Reseach Article

Barcode Localization using Curvelet Transform and Neural Network

by Priyanka Gaur, Shamik Tiwari
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 85 - Number 6
Year of Publication: 2014
Authors: Priyanka Gaur, Shamik Tiwari
10.5120/14843-3083

Priyanka Gaur, Shamik Tiwari . Barcode Localization using Curvelet Transform and Neural Network. International Journal of Computer Applications. 85, 6 ( January 2014), 6-9. DOI=10.5120/14843-3083

@article{ 10.5120/14843-3083,
author = { Priyanka Gaur, Shamik Tiwari },
title = { Barcode Localization using Curvelet Transform and Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 85 },
number = { 6 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 6-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume85/number6/14843-3083/ },
doi = { 10.5120/14843-3083 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:01:44.069904+05:30
%A Priyanka Gaur
%A Shamik Tiwari
%T Barcode Localization using Curvelet Transform and Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 85
%N 6
%P 6-9
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Barcode localization is the main challenge in developing an image-based barcode reading system. Bar codes are able to carry both explicit information and a database key, by encoding a series of characters or symbols. This paper deals with localization of European Article Number-13 (EAN-13) barcode in an image. A new approach for detecting and locating bar-codes is introduced here, which is based on the curvelet transform. All extracted feature by curvelet transform are applied to the neural network for training and testing. The performance of the proposed work shows efficient result.

References
  1. Rocholl, J. C. , Klenk and Heidemann, "Robust 1D Barcode Recognition on Mobile Devices", in Pattern Recognition (ICPR), 2010 20th International Conference, Istanbul, ©IEEE. doi:10. 1109/ICPR. 2010. 664.
  2. En Peng, Peursum. P. and Ling Li, "Product Barcode and Expiry Date Detection for the Visually Impaired Using a Smartphone", in Digital image computing techniques and applications(DICTA), 2012 international conference, Fremantle, WA, ©IEEE, doi : 10. 1109/DICTA 2012. 6411673.
  3. Chai and Hock, "Locating and Decoding EAN-13 Barcodes from Images Captured by Digital Cameras", in Information, Communications and Signal Processing, 2005 Fifth International Conference, Bangkok, ©IEEE, doi:10. 1109/ICICS. 2005. 1689328 .
  4. Katona, Nyul and L. G. ,"A Novel Method for Accurate and Efficient Barcode Detection with Morphological Operations", in Signal Image Technology and Internet Based Systems (SITIS), 2012 Eighth International Conference , Naples ,©IEEE, doi : 10. 1109/SITIS. 2012. 53 .
  5. E. J. Candes, D. L. Donoho, Curvelets, multi-resolution representation, and scaling laws, Wavelet Applications in Signal and Image Processing VIII, Vol. 4119-01, SPIE, 2000
  6. Guesmi, Tunisia, Trichili, Alimi and Solaiman, "Curvelet transform-based features extraction for fingerprint identification", in Biometrics Special Interest Group (BIOSIG)-Proceedings of the International Conference, 2012, Darmstadt.
  7. AlZubi, Sharif, M. S. ,Islam, N. and Abbod, M. ,"Multi-resolution analysis using curvelet and wavelet transforms for medical imaging", in Medical Measurements and Applications Proceedings (MeMeA), 2011 IEEE International Workshop, 2011,Bari, ©IEEE, doi:10. 1109/MeMeA. 2011. 5966687
  8. Haykin Simon, NEURAL NETWORKS: a comprehensive foundation. Prentice Hall PTR . 1994.
  9. Svozil, Daniel, Vladimir Kvasnicka, and Jir?í Pospichal, "Introduction to multi-layer feed-forward neural networks", in Chemometrics and intelligent laboratory systems 39. 1 (1997): 43-62.
Index Terms

Computer Science
Information Sciences

Keywords

EAN-13 Barcode Curvelet transform Neural Network.