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A Method for 2D Bar Code Recognition by Using Rectangle Features to Allocate Vertexes

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3926))

Abstract

This paper describes a method of image processing for the 2D bar code image recognition, which is capable of processing images extremely rapidly and achieving high recognition rate. This method includes three steps. The first step is to find out the four vertexes of ROI (Regions Of Interest); the second is a geometric transform to form an upright image of ROI; the third is to restore a bilevel image of the upright image. This work is distinguished by a key contribution, which is used to find the four vertexes of ROI by using an integrated feature. The integrated feature is composed of simple rectangle features, which are selected by the AdaBoost algorithm. To calculate these simple rectangle features rapidly, the image representation called "Integral Image" is used.

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References

  1. Ouaviani, E., Pavan, A., Bottazzi, M., Brunelli, E., Caselli, F., Guerrero, M.: A Common Image Processing Framework for 2D Barcode Reading. In: Proc. of the Seventh International Conference on Image Processing and Its Applications (Conf. Publ. No. 465), vol. 2(13-15), pp. 652–655 (1999)

    Google Scholar 

  2. Otsu, N.: A Threshold Selection Method from Gray Level Histogram. IEEE Transactions on SMC (9) (1979)

    Google Scholar 

  3. Normand, N., Viard-Gaudin, C.: A Two-Dimensional Bar Code Reader. In: Proceedings of the 12th International Conference on Pattern Recognition (Signal Processing), vol. 3, pp. 201–203 (1994)

    Google Scholar 

  4. Viola, P., Jones, M.: Rapid Object Detection Using a Boosted Cascade of Simple Features. In: Proc. CVPR (2001)

    Google Scholar 

  5. Freund, Y., Schapire, R.E.: A Decision-Theoretic Generalization of On-line Learning and an Application to Boosting. Journal of Computer and System Sciences (1997)

    Google Scholar 

  6. Papageorgious, C., Oren, M., Poggio, T.: A General Framework for Object Detection. In: Proceedings of International Conference on Computer Vision (1998)

    Google Scholar 

  7. Sonka, M., Hlavac, V., Boyle, R.: Image Processing, Analysis, and Machine Vision, 2nd edn., pp. 62–65. Brochs/Cole (2000)

    Google Scholar 

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© 2006 Springer-Verlag Berlin Heidelberg

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Heping, Y., Wang, Z., Guo, S. (2006). A Method for 2D Bar Code Recognition by Using Rectangle Features to Allocate Vertexes. In: Liu, W., Lladós, J. (eds) Graphics Recognition. Ten Years Review and Future Perspectives. GREC 2005. Lecture Notes in Computer Science, vol 3926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11767978_9

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  • DOI: https://doi.org/10.1007/11767978_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34711-8

  • Online ISBN: 978-3-540-34712-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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