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Automatic Text Recognition Using Difference Ratio

  • Shamama AnwarEmail author
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 77)

Abstract

With the rapid advancement in technology, digitization of documents is gaining popularity. For digitization, the printed or handwritten text needs to be converted to a computer-readable form. For this, the document has to go through line detection, character extraction, recognition and finally conversion to a computer-readable form. A variety of methods have been proposed for the same. The paper proposes a method for text extraction and recognition which is based on a data set called as a learn file which is a vector representation of the images in the data set. Recognition is achieved by using the difference ratio between the input image and the learn file. The paper also presents two applications of the proposed method: text extraction from printed document and automatic number plate recognition. After recognition, the identified characters are written on to a text file.

Keywords

Text recognition Text extraction Absolute difference Difference ratio Automatic number plate recognition 

References

  1. 1.
    Sobottka, K., Bunke, H., Kronenberg, H.: Identification of text on colored book and journal covers. In: International Conference on Document Analysis and Recognition, p. 57 (1999)Google Scholar
  2. 2.
    Shi, Z., Setlur, S., Govindaraju, V.: Text extraction from gray scale historical document images using adaptive local connectivity map. In: 8th International Conference on Document Analysis and Recognition, pp. 794–798 (2005)Google Scholar
  3. 3.
    Zhan, Y., Wang, W., Gao, W.: A robust split- and -merge text segmentation approach for images. In: 18th International Conference on Pattern Recognition, vol. 2, pp. 1002–1005 (2006)Google Scholar
  4. 4.
    Nagabhushan, P., Nirmala, S.: Text extraction in complex color document images for enhanced readability. Intell. Inf. Manag. 2(2), 120–133 (2010)Google Scholar
  5. 5.
    Zaravi, D., Rostami, H., Malahzaheh, A., Mortazavi, S.S.: Journals subheadlines text extraction using wavelet thresholding and new projection profile. Int. J.Comput. Electr. Autom. Control Inf. Eng. 5(1), 33–36 (2011)Google Scholar
  6. 6.
    Sumathi, C.P., Santhanam, T., Devi, G.G.: A survey on various approached of text extraction in images. Int. J. Comput. Sci. Eng. Surv. 3(4), 27–42 (2012)CrossRefGoogle Scholar
  7. 7.
    Badr, A., Abdelwahab, M.M., Thabet, A.M., Abdelsadek, A.M.: Automatic number plate recognition system. Math. Comput. Sci. Ser. 38(1), 62–71 (2011)MathSciNetzbMATHGoogle Scholar
  8. 8.
    Kranthi, S., Pranathi, K., Srisaila, A.: Automatic number plate recognition. Int. J. Adv. Technol. 2(3), 408–422 (2011)Google Scholar
  9. 9.
    Hoang, T.V., Tabbone, S.: Text extraction from graphical document images using sparse representation. In: 9th International Workshop on Document Analysis System, pp. 143–150 (2010)Google Scholar
  10. 10.
    Grover, S., Arora, K., Mitra, S.K.: Text extraction from documnet images using edge information. In: Annual IEEE India Conference, pp. 1–4 (2009)Google Scholar
  11. 11.
    Kocer, H.E., Cevik, K.K.: Artificial neural networks based vehicle license plate recognition. Procedia Comput. Sci. 3, 1033–1037 (2011)CrossRefGoogle Scholar
  12. 12.
    Roy, A., Ghoshal, D.P.: Number plate recognition for use in different countries using an improved segmentation. In: 2nd National Conference on Emerging Trends and Applications in Computer Science, pp. 1–5 (2011)Google Scholar
  13. 13.
    Patel, C., Shah, D., Patel, A.: Automatic number plate recognition system (ANPR): a survey. Int. J. Comput. Appl. 69(9), 21–33 (2013)Google Scholar
  14. 14.
    Singla, N.: Motion detection based on frame difference method. Int. J. Inf. Comput. Technol. 4(15), 1559–1565 (2014)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringBirla Institute of TechnologyRanchiIndia

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