IDEAS home Printed from https://ideas.repec.org/a/rau/journl/v10y2016i1p240-252.html
   My bibliography  Save this article

Ocr Quality Improvement Using Image Preprocessing

Author

Listed:
  • Vlad Badoiu

    (”Politehnica” University of Bucharest, Bucharest, Romania)

  • Andrei-Constantin Ciobanu

    (”Politehnica” University of Bucharest, Bucharest, Romania)

  • Sergiu Craitoiu

    (”Politehnica” University of Bucharest, Bucharest, Romania)

Abstract

Optical character recognition (OCR) remains a difficult problem for noisy documents or documents scanned at low resolution. Many current approaches rely on stored font models that are vulnerable to cases in which the document is noisy or is written in a font dissimilar to the stored fonts. In this paper we test two approaches for preprocessing, or correcting the input images. The focus is on noise reduction, lightness correction and binarization, all relative to found letters with a slow but more accurate method and a fast and less accurate method. We then compare the results and see if the extra time spent in developing more complex letter deduction technique offers significant improvements.

Suggested Citation

  • Vlad Badoiu & Andrei-Constantin Ciobanu & Sergiu Craitoiu, 2016. "Ocr Quality Improvement Using Image Preprocessing," Romanian Economic Business Review, Romanian-American University, vol. 10(1), pages 240-252, May.
    • Handle: RePEc:rau:journl:v:10:y:2016:i:1:p:240-252
    as

    Download full text from publisher

    File URL: http://www.rebe.rau.ro/RePEc/rau/jisomg/SU16/JISOM-SU16-A23.pdf
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rau:journl:v:10:y:2016:i:1:p:240-252. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Alex Tabusca (email available below). General contact details of provider: https://edirc.repec.org/data/firauro.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.