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Restoration of Blurred Binary Images Using Discrete Tomography

  • Jozsef Nemeth
  • Peter Balazs
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8192)

Abstract

Enhancement of degraded images of binary shapes is an important task in many image processing applications, e.g. to provide appropriate image quality for optical character recognition. Although many image restoration methods can be found in the literature, most of them are developed for grayscale images. In this paper we propose a novel binary image restoration algorithm. As a first step, it restores the projections of the shape using 1-dimensional deconvolution, then reconstructs the image from these projections using a discrete tomography technique. The method does not require any parameter setting or prior knowledge like an estimation of the signal-to-noise ratio. Numerical experiments on a synthetic dataset show that the proposed algorithm is robust to the level of the noise. The efficiency of the method has also been demonstrated on real out-of-focus alphanumeric images.

Keywords

Binary Image Synthetic Dataset Image Restoration Optical Character Recognition Projection Vector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jozsef Nemeth
    • 1
  • Peter Balazs
    • 2
  1. 1.Department of Computer Algorithms and Artificial IntelligenceUniversity of SzegedSzegedHungary
  2. 2.Department of Image Processing and Computer GraphicsUniversity of SzegedSzegedHungary

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