Home
  • English
  • ÄŒeÅ¡tina
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • LatvieÅ¡u
  • Magyar
  • Nederlands
  • Português
  • Português do Brasil
  • Suomi
  • Log In
    New user? Click here to register. Have you forgotten your password?
Home
  • Browse Our Collections
  • Publications
  • Researchers
  • Research Data
  • Institutions
  • Statistics
    • English
    • ÄŒeÅ¡tina
    • Deutsch
    • Español
    • Français
    • Gàidhlig
    • LatvieÅ¡u
    • Magyar
    • Nederlands
    • Português
    • Português do Brasil
    • Suomi
    • Log In
      New user? Click here to register. Have you forgotten your password?
  1. Home
  2. Resources
  3. UniMAP Index Publications
  4. Publications 2018
  5. Improved Feng Binarization Based on Max-Mean Technique on Document Image
 
Options

Improved Feng Binarization Based on Max-Mean Technique on Document Image

Journal
2018 International Conference on Computational Approach in Smart Systems Design and Applications, ICASSDA 2018
Date Issued
2018-09-28
Author(s)
Mustafa W.A.
Khairunizam W.
Ibrahim Z.
Shahriman A.B.
Razlan Z.M.
DOI
10.1109/ICASSDA.2018.8477616
Handle (URI)
https://hdl.handle.net/20.500.14170/11986
Abstract
Many valuable documents stored on the libraries and to keep the historical document content safe, a binarization approach on document images must be applied. In this study, a modification of Feng algorithm using Max-Mean was proposed. Feng method produced a blurred image and introduced a noise in the resulting image. The proposed method successfully to overcome the Feng method problem by suggesting a maximum threshold value. Based on the result, Max-Mean method able to improve the image quality and reduced the noise. Based on IQA, the proposed method achieved F-measure (74.901), PSNR (16.104), NRM (0.153) and MPM (1.371). Accuracy also shows the increment compare to the Feng result.
Subjects
  • Binarization | Docume...

Thumbnail Image
google-scholar
Views
Downloads
  • About Us
  • Contact Us
  • Policies