CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

A Study on Multiple Barcode Detection from an Image in Business System

by Atiqul Islam Chowdhury, Mushfika Sharmin Rahman, Nazmus Sakib
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 37
Year of Publication: 2019
Authors: Atiqul Islam Chowdhury, Mushfika Sharmin Rahman, Nazmus Sakib
10.5120/ijca2019918340

Atiqul Islam Chowdhury, Mushfika Sharmin Rahman, Nazmus Sakib . A Study on Multiple Barcode Detection from an Image in Business System. International Journal of Computer Applications. 181, 37 ( Jan 2019), 30-37. DOI=10.5120/ijca2019918340

@article{ 10.5120/ijca2019918340,
author = { Atiqul Islam Chowdhury, Mushfika Sharmin Rahman, Nazmus Sakib },
title = { A Study on Multiple Barcode Detection from an Image in Business System },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2019 },
volume = { 181 },
number = { 37 },
month = { Jan },
year = { 2019 },
issn = { 0975-8887 },
pages = { 30-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number37/30275-2019918340/ },
doi = { 10.5120/ijca2019918340 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:08:25.589633+05:30
%A Atiqul Islam Chowdhury
%A Mushfika Sharmin Rahman
%A Nazmus Sakib
%T A Study on Multiple Barcode Detection from an Image in Business System
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 37
%P 30-37
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The pillar of automatic identification is Barcode technology which is used comprehensively in real time applications with various types of codes. The different types of codes and applications sometimes faces special problems, so the improvement of the effectiveness must be done persistently. This paper’s proposal mainly deals with multiple product’s barcode to be detected simultaneously. The proposed algorithm which will have implementation for supershop billing system and inventory management. The method will recognize the barcodes using image processing. Images will be taken using mobile camera sensor. It will detect 1D barcodes such as EAN-13 barcodes, Code-128 barcodes, 2D barcodes such as QR codes. Moreover, it will be angle invariant, requires less user interaction than usual and can be executed on available computers. This model helps consumers to minimize the time for the billing system in shopping. We have implemented this in Python IDE using OpenCV library.

References
  1. [A. N. K. A. U. N. R. A. M. R. Sampada S. Upasani, "Robust Algorithm for Developing Barcode Recognition System using Web-cam," International Journal of Scientific & Engineering Research, vol. 7, no. 4, pp. 82-86, April 2016.
  2. K. V. Gowtham M N, "Generating EAN-13 Standard Barcodes," International Journal of Science and Research (IJSR), vol. 3, no. 6, pp. 1307-1309, 2014.
  3. M. K. a. L. ́. ́. G. N. ́ul, "Efficient 1D and 2D barcode detection using mathematical morphology".
  4. H. J. G. Kinjal H. Pandya, "A Survey on QR Codes: in context of Research and Application," International Journal of Emerging Technology and Advanced Engineering, vol. 4, no. 3, pp. 258-262, 2014.
  5. K.-T. W. M.-C. W. N.-Y. C. J.-H. W. Chun-Shun Tseng, "Retrospective Tracking for Barcode Reading," IEEE, pp. 114-119, 2010.
  6. Z. S. D. S. H. Xiaochao Li, "Reconstruct Algorithm of 2D barcode for Reading the QR Code on Cylindrical Surface," The Natural Science Foundation of China.
  7. Y. Z. a. T. Lu, "A Fast Color Barcode Detection Method through Cross," 13th International Conference on Document Analysis and Recognition (ICDAR), pp. 416-420, 2015.
  8. S.-C. L. a. P.-H. Wang, "Design of a barcode identification system," Consumer Electronics-Taiwan (ICCE-TW), IEEE International Conference, pp. 237-238, 2014.
  9. I. G. a. S. A. Alessandro Zamberletti, "Robust angle invariant 1d barcode detection," 2nd IAPR Asian Conference, pp. 160-164, 2013.
  10. C Galamhos, Jose Matas, and Josef Kittler. “Progressive probabilistic hough transform for line detection,” Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on., volume 1, pages 554–560. IEEE, 1999.
  11. Robert Adelmann, Marc Langheinrich, and Christian Floerkemeier. “Toolkit for bar code recognition and resolving on camera phones-jump starting the internet of things,” GI Jahrestagung (2), 94:366–373, 2006.
  12. Timothy R Tuinstra. “Reading barcodes from digital imagery,” PhD thesis, PhD thesis, Cedarville University, 2006.
  13. Alessandro Zamberletti, Ignazio Gallo, Moreno Carullo and Elisabetta 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
Index Terms

Computer Science
Information Sciences

Keywords

Image processing barcode EAN-13 QR code ZBar.

Powered by PhDFocusTM