IDEAS home Printed from https://ideas.repec.org/a/jbh/ijsrcs/v8y2022i6idhcseit228652.html

Text Recognition Using Image Processing Technology for Visiting Card

Author

Listed:
  • Meera Sawalkar
  • udula Chaudhari
  • Sarang Joshi
  • Yash Raut
  • Shaurya Shrivastav

Abstract

Image recognition and optical character recognition technologies have become an integral part of our daily lives due to increasing computing power and the proliferation of scanning devices. A printed document can be quickly converted to a digital text file using optical character recognition and edited by the user. The time required to digitize documents is therefore minimal. This is especially useful when archiving large print volumes. In this study, we show how image processing techniques can be used in combination with optical character recognition to improve recognition accuracy and improve efficiency in extracting text from images. Two of his software systems are developed and tested in this study: a character recognition system applied to cosmetics-related advertising images and a recognition and text recognition system for natural scenes. Experimental results show that the proposed system can accurately recognize text in images.

Suggested Citation

  • Meera Sawalkar & udula Chaudhari & Sarang Joshi & Yash Raut & Shaurya Shrivastav, 2022. "Text Recognition Using Image Processing Technology for Visiting Card," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 8(6), pages 488-492, December.
  • Handle: RePEc:jbh:ijsrcs:v8:y2022:i6:id:hcseit228652
    DOI: 10.32628/CSEIT228652
    Note: Article URL: https://ijsrcseit.com/CSEIT228652
    as

    Download full text from publisher

    File URL: https://ijsrcseit.com/CSEIT228652
    File Function: Article URL
    Download Restriction: no

    File URL: https://ijsrcseit.com/paper/CSEIT228652.pdf
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.32628/CSEIT228652?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    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:jbh:ijsrcs:v8:y2022:i6:id:hcseit228652. 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: Pankaj Sharma (USA) (email available below). General contact details of provider: https://ijsrcseit.com/home .

    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.