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Article
Sparsity-Based Edge Noise Removal from Bilevel Graphical Document Images
International Journal on Document Analysis and Recognition (IJDAR)
  • Thai V. Hoang, Inria Nancy
  • Elisa H. Barney Smith, Boise State University
  • Salvatore Tabbone, UniversitĂ© de Lorraine
Document Type
Article
Publication Date
10-1-2013
DOI
http://dx.doi.org/10.1007/s10032-013-0213-4
Abstract

This paper presents a new method to remove edge noise from graphical document images using geometrical regularities of the graphics contours that exist in the images. Denoising is understood as a recovery problem and is accomplished by employing a sparse representation framework in the form of a basis pursuit denoising algorithm. Directional information of the graphics contours is encoded by atoms in an overcomplete dictionary which is designed to match the input data. The optimal precision parameter used in this framework is shown to have a linear relationship with the level of the noise that exists in the image. Experimental results show the superiority of the proposed method over existing ones in terms of image recovery and contour raggedness.

Citation Information
Thai V. Hoang, Elisa H. Barney Smith and Salvatore Tabbone. "Sparsity-Based Edge Noise Removal from Bilevel Graphical Document Images" International Journal on Document Analysis and Recognition (IJDAR) (2013)
Available at: http://works.bepress.com/elisa_barney_smith/124/