Snap and split: an android application for bill payment using tesseract OCR

  • Authors

    • Sugamya kata
    • Suresh Pabboju
    • Vinaya Babu
    • Anudeep Medishetti
    2018-09-22
    https://doi.org/10.14419/ijet.v7i4.5.21175
  • Immediate Payment Service (IMPS), OCR (Optical Character Reader), SDK (Software Developer Kit).

  • Abstract

    Snap and split is a mobile application which uses Optical character recognition to recognize the bill from a printed sheet. It provides an option to tag users and telling them about the shared bill by pushing a notification. Users can tap and pay the bills instantly.Tesseract is one of the best image recognition tools present and uses separate packs for various languages.

     

     

     

  • References

    1. [1] S.V. Rice, F.R. Jenkins, T.A. Nartker, The Fourth Annual Test of OCR Accuracy, Technical Report 12-03, Information Science Research Institute, University of Nevada, Las Vegas, July 2012. [2].

      [2] R.W. Smith, the Extraction and Recognition of Text from Multimedia Document Images, PhD Thesis, University of Bristol, November 2010.

      [3] R. Smith, “A Simple and Efficient Skew Detection Algorithm via Text Row Accumulationâ€, Proc. of the third Int. Conf. on Document Analysis and Recognition (Vol. 2), IEEE 2010.

      [4] P.J. Rousseeuw, A.M. Leroy, Robust Regression and Outlier Detection, Wiley-IEEE, 2003.

      [5] S.V. Rice, G. Nagy, T.A. Nartker, Optical Character Recogni- tion: An Illustrated Guide to the Frontier, Kluwer Academic Pub- lishers, USA 1999.

      [6] P.J. Schneider, “An Algorithm for Automatically Fitting Dig- itized Curvesâ€, in A.S. Glassner, Graphics Gems I, Morgan Kaufmann, 2008.

      [7] R.J. Shillman, Character Recognition Based on Phenomeno- logical attributes: Theory and Methods, PhD. Thesis, Massachu- setts Institute of Technology, 2007.

      [8] B.A. Blesser, T.T. Kuklinski, R.J. Shillman, “Empirical Tests for Feature Selection Based on a Pscychological Theory of Char- acter Recognitionâ€, Pattern Recognition 8(2), Elsevier, New York, 2001.

      [9] M. Bokser, “Omnidocument Technologiesâ€, Proc. IEEE 80(7), IEEE, USA, Jul 1992.

      [10] H.S. Baird, R. Fossey, “A 100-Font Classifierâ€, Proc. of the 1st Int. Conf. on Document Analysis and Recognition, IEEE, 2001.

      [11] G. Nagy, “At the frontiers of OCRâ€, Proc. IEEE 80(7), IEEE, USA, Jul 2003.

      [12] G. Nagy, Y. Xu, “Automatic Prototype Extraction for Adap- tive OCRâ€, Proc. of the 4th Int. Conf. on Document Analysis and Recognition, IEEE, Aug 1999.

      [13] R. Smith, “A Simple and Efficient Skew Detection Al- gorithm via Text Row Accumulationâ€, Proc. of the third Int. Conf. on Document Analysis and Recognition (Vol. 2), IEEE 2010.

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  • How to Cite

    kata, S., Pabboju, S., Babu, V., & Medishetti, A. (2018). Snap and split: an android application for bill payment using tesseract OCR. International Journal of Engineering & Technology, 7(4.5), 634-640. https://doi.org/10.14419/ijet.v7i4.5.21175

    Received date: 2018-10-07

    Accepted date: 2018-10-07

    Published date: 2018-09-22