• DocumentCode
    3581300
  • Title

    Degradation enhancement for the captured document image using retinex theory

  • Author

    Wagdy, Marian ; Faye, Ibrahima ; Rohaya, Dayang

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Univ. Teknol. Petronas, Tronoh, Malaysia
  • fYear
    2014
  • Firstpage
    363
  • Lastpage
    367
  • Abstract
    The state-of-arts global thresholding techniques are fast and efficient to convert the gray scale document image into a binary image. However, they are unsuitable for complex and degraded documents. Moreover, global thresholding techniques produce border noise when the illumination of the document is not uniform. Other methods that depend on local thresholding techniques are efficient in the case of degraded document images, but have common disadvantages include the dependence on the region size and the image characteristics, and the computational time. In this paper we propose a method to overcome the limitations of the related global and local threshold techniques by using the concept of Retinex theory based on Median filter which can effectively enhance the degraded and poor quality document image. High quality results in terms of visual criteria and OCR performance is produced compared to the previous works.
  • Keywords
    document image processing; image segmentation; median filters; optical character recognition; OCR performance; Retinex theory; binary image; captured document image; degradation enhancement; degraded document images; global thresholding techniques; gray scale document image; local thresholding techniques; median filter; Degradation; Filtering theory; Lighting; Noise; Optical character recognition software; Text analysis; Retinex theory; binarization; degradation enhancement; global thresholding; local thresholding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Multimedia (ICIMU), 2014 International Conference on
  • Type

    conf

  • DOI
    10.1109/ICIMU.2014.7066660
  • Filename
    7066660