IDEAS home Printed from https://ideas.repec.org/a/igg/japuc0/v7y2015i3p13-24.html
   My bibliography  Save this article

Direct Part Mark Bar Code Image Preprocessing

Author

Listed:
  • Lingling Li

    (Department of Automation, North China Electric Power University, Baoding, China)

  • Tao Gao

    (Department of Automation, North China Electric Power University, Baoding, China & Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand)

  • Yaoquan Yang

    (Department of Automation, North China Electric Power University, Baoding, China)

Abstract

Due to factors such as ambient light and metal materials, the collected industrial DPM bar code images may exist uneven illumination, low contrast, color of background area is darker than bar code region and other harsh issues, while the existing 2D code recognition device can only recognize the type which bar code area color is darker than background region. Therefore, the quality of preprocessing effect is the key point to subsequent recognition algorithm. In this paper, the homomorphic filtering method is used to weaken the influence of uneven illumination firstly, which will enhance the image contrast degree. Then do horizontal and vertical projection, find the points with greater intensity changes in both directions, make the image into blocks, again use the classic Kittler binarization algorithm on each block, then use mathematical morphology method to standardize the dot data matrix images. Finally, an improved Hough transform method is used to detect the ‘L' type finder pattern accurately, then find its pixel value, if color of the background region is darker than the bar code area, do invert-color processing. The processing results of a set of industrial DPM bar code images confirm the effectiveness of the proposed method.

Suggested Citation

  • Lingling Li & Tao Gao & Yaoquan Yang, 2015. "Direct Part Mark Bar Code Image Preprocessing," International Journal of Advanced Pervasive and Ubiquitous Computing (IJAPUC), IGI Global, vol. 7(3), pages 13-24, July.
  • Handle: RePEc:igg:japuc0:v:7:y:2015:i:3:p:13-24
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJAPUC.2015070102
    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:igg:japuc0:v:7:y:2015:i:3:p:13-24. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.