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A Novel Method for Barcode Localization in Image Domain

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Image Analysis and Recognition (ICIAR 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7950))

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Abstract

Barcode localization is an essential step of the barcode reading process. For industrial environments, having high-resolution cameras and eventful scenarios, fast and reliable localization is crucial. Images acquired in those setups have limited parameters, however, they vary at each application. In earlier works we have already presented various barcode features to track for localization process. In this paper, we present a novel approach for fast barcode localization using a limited set of pixels in image domain.

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References

  1. Adelmann, R.: Toolkit for bar code recognition and resolving on camera. In: Phones Jump Starting the Internet of Things. Informatik 2006 Workshop on Mobile and Embedded Interactive Systems (2006)

    Google Scholar 

  2. Tuinstra, T.R.: Reading Barcodes from Digital Imagery. PhD thesis, Cedarville University (2006)

    Google Scholar 

  3. Tekin, E., Coughlan, J.M.: An algorithm enabling blind users to find and read barcodes. In: 2009 Workshop on Applications of Computer Vision (WACV), pp. 1–8 (December 2009)

    Google Scholar 

  4. Tekin, E., Coughlan, J.M.: A mobile phone application enabling visually impaired users to find and read product barcodes. In: Miesenberger, K., Klaus, J., Zagler, W., Karshmer, A. (eds.) ICCHP 2010, Part II. LNCS, vol. 6180, pp. 290–295. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  5. Tekin, E., Coughlan, J.: A bayesian algorithm for reading 1d barcodes. In: Proceedings of the 2009 Canadian Conference on Computer and Robot Vision, CRV 2009, pp. 61–67. IEEE Computer Society, Washington, DC (2009)

    Chapter  Google Scholar 

  6. Gallo, O., Manduchi, R.: Reading 1d barcodes with mobile phones using deformable templates. IEEE Trans. Pattern Anal. Mach. Intell. 33(9), 1834–1843 (2011)

    Article  Google Scholar 

  7. Wang, K., Zou, Y., Wang, H.: Bar code reading from images captured by camera phones. In: 2005 2nd International Conference on Mobile Technology, Applications and Systems, p. 6 (November 2005)

    Google Scholar 

  8. Shams, R., Sadeghi, P.: Bar code recognition in highly distorted and low resolution images. In: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2007, vol. 1, pp. I–737 –I–740 (April 2007)

    Google Scholar 

  9. Bodnár, P., Nyúl, L.G.: Improving barcode detection with combination of simple detectors. In: The 8th International Conference on Signal Image Technology, SITIS 2012, pp. 300–306 (2012)

    Google Scholar 

  10. Lin, D.-T., Lin, M.-C., Huang, K.-Y.: Real-time automatic recognition of omnidirectional multiple barcodes and dsp implementation. Machine Vision and Applications 22, 409–419 (2011), doi:10.1007/s00138-010-0299-3

    Article  Google Scholar 

  11. Qi, X., Juett, J.: Barcode localization using bottom-hat filter. NSF Research Experience for Undergraduates (2005)

    Google Scholar 

  12. Katona, M., Nyúl, L.G.: A novel method for accurate and efficient barcode detection with morphological operations. In: The 8th International Conference on Signal Image Technology, SITIS 2012, pp. 307–314 (2012)

    Google Scholar 

  13. Youssef, S.M., Salem, R.M.: Automated barcode recognition for smart identification and inspection automation. Expert Systems with Applications 33(4), 968–977 (2007)

    Article  Google Scholar 

  14. Bodnár, P., Nyúl, L.G.: Barcode detection with morphological operations and clustering. In: Proceedings of the Ninth IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, pp. 51–57 (2012)

    Google Scholar 

  15. Śimurda, P.: Barcode localization in image. Information Sciences and Technologies Bulletin of the ACM Slovakia 3, 55–56 (2011)

    Google Scholar 

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Bodnár, P., Nyúl, L.G. (2013). A Novel Method for Barcode Localization in Image Domain. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2013. Lecture Notes in Computer Science, vol 7950. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39094-4_22

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  • DOI: https://doi.org/10.1007/978-3-642-39094-4_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39093-7

  • Online ISBN: 978-3-642-39094-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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